Amazon.com
"Intended as an upper-level undergraduate or introductory graduate text in computer science theory," this book lucidly covers the key concepts and theorems of the theory of computation. The presentation is remarkably clear; for example, the "proof idea," which offers the reader an intuitive feel for how the proof was constructed, accompanies many of the theorems and a proof. Introduction to the Theory of Computation covers the usual topics for this type of text plus it features a solid section on complexity theory--including an entire chapter on space complexity. The final chapter introduces more advanced topics, such as the discussion of complexity classes associated with probabilistic algorithms.
Book Description
This highly anticipated revision builds upon the strengths of the previous edition. Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.
Customer Reviews:
My choice for textbook in my computation theory class.......2007-10-01
I recently encountered this book at a publisher's booth at a computer conference and read it on the ride back home. This morning I made a trip to the college bookstore and notified them that it is the textbook that I will be using in my computation theory class this spring.
The chapter titles are:
0) Introduction - this chapter contains the fundamental mathematical background of sets, functions, graphs and proofs. For most students, it could be skipped or skimmed.
1) Regular languages - this chapter is an introduction to deterministic and nondeterministic finite automata and regular expressions.
2) Context-free languages - an introduction to context-free grammars and pushdown automata.
3) The Church-Turing theses - an introduction to Turing machines and the variants, such as multiple tapes and nondeterministic Turing machines.
4) Decidability - the definition of decidability and how Turing machines and finite automata are used to prove or disprove if a language is decidable.
5) Reducibility - the definition of reducible and how Turing machines can be used to execute reductions.
6) The recursion theorem - an introduction to the recursion theorem and some applications to formal theories.
7) Time complexity - the first chapter in the coverage of algorithmic complexity, in this case execution time.
8) Space complexity - an examination of the complexity of algorithms from the perspective of the amount of memory required.
9) Intractability - an examination of the problems that can be solved in principle but not in practice.
10) Advanced topics in complexity theory - approximation algorithms, probabilistic algorithms, alternation, interactive proof systems, parallel computation and cryptography.
There is less coverage of grammars than most books, which is replaced by more in the area of algorithmic analysis. In my opinion, that is an appropriate tradeoff, the analysis of algorithms gives the students some understanding of how automata are applied in computer science.
Another excellent feature of this book is the solutions to selected exercises that appear at the end of the chapters. My estimate is that reasonably detailed solutions to approximately one-third of the problems are included. This allows the students to work extra problems by themselves, and helps the instructor if they are asked to do another example in class that they have not already worked through.
The exposition is very good; I am convinced that the students will be able to read the material on their own, which is one more reason why I adopted this book for my course.
well-organized, progressive, and understandable.......2007-01-06
As an intro to the theoretical background to computer science goes, this book is about as readable and approachable as you can get.
It gives a very thorough treatment of the whole theoretical basis, from regular languages and pumping lemmas out through Turing machines and related issues, and on to some interesting language classes (like NP and PSpace-complete).
If there's a single sticking point with the book, it's that it insists on a very strict formalism (ie: everything is proof-based) -- something necessary for the topic, but it sometimes renders the material a bit hard to digest.
Great book on the subject.......2006-12-27
If you are interested in or for other reasons must read a book on this subject, this is the book. I took a class last semester which used Hopcroft as the text and I found myself often turning to this book for better understanding. This book is more intuitive and thus a bit less formal than Hopcroft but when trying to learn, understanding is better than mathematical formalism. If you are new to the subject, Sipser is the book to begin with.
Very readable, diverse, and a little sparse.......2006-11-25
This is a wonderful little gem of a book that presents the theory of computation in a fascinating way. It is targeted at advanced undergraduates in computer science, but assumes remarkably little prior knowledge, making it accessible to nearly anyone. The book covers a lot of ground, including the standard fare of automata, computability, and complexity results, plus some bonus material such as probablistic and parallel complexity, information theory, decidable logical theories, and other topics that are normally left out of introductory books. On top of this, the book is remarkably thin!
The best attribute of Sipser's book, though, is the engaging style. This is an easy book to read. You will not feel like you're running into a brick wall, as is sometimes the case with books on abstract topics. It's not so much that the book is slow or gentle (it's really not) as that it is interesting, engaging, and has a knack for stopping short of getting too caught up in details. A number of small things -- the occasional amusing exercise, the "proof idea" sections, or helpful pictures -- add up to an enjoyable reading experience.
Two cautions are appropriate to students considering this book. First, there are variations between authors in the definitions of various automata (especially PDAs). The differences are trivial, and more a matter of taste than of any real importance; but it could come up if you use Sipser as a supplement to a course that follows a different textbook. Second, the coverage of many topics in Sipser's book is brief and concise, sometimes more than you might like. Some important concepts (for example, pairwise distinguishability of strings) are only mentioned in exercises, not in the main chapter, so at least skim all the exercises even if you don't do them. The sketchy coverage is especially pronounced in advanced topics, so (as always) expect to do some filling in of concepts if you go on into further study of this area.
Most appropriate for CS students.......2006-06-01
As a teacher of the subject, I have had the chance to evaluate numerous books on the theory of computation. Of all the available texts, I think this one is the most appropriate for CS students. In the past I taught out of Dexter Kozen's book, which is incredibly elegant, but had some resistance from the students. Thinking it over I decided that Kozen's text, although beautiful, may be better suited to students pursuing a degree in pure math. Sipser's book, on the other hand, is more gentle. I find that Sipser demands far less mathematical maturity from his readers, and thus allows the difficulty to be shifted from excessive formalism to the inherent challenges present in the material. In addition, following Sipser's treatment, I was able to cover finite state machines and pushdown automata in far less time, thus allowing me to concentrate on computability and beyond. The book really shines in its treatment of computability theory, eloquently directing attention to some of the most beautiful aspects.
Another benefit of Sipser's book is the exercises, of which there are many more in this edition. Someone studying on their own should find the initial group of exercises in each section quite approachable. Even the more challenging problems are not incredibly hard, and typically draw their difficulty from the deeper themes of the chapter instead of obscure details.
If you are looking for an enjoyable, well-paced book with an introduction to computability and complexity that is truly inspiring, this is the one for you. A mathematician looking for a bit more rigor may do better with Kozen.
Book Description
When you think about how far and fast computer science has progressed in recent years, it's not hard to conclude that a seven-year old handbook may fall a little short of the kind of reference today's computer scientists, software engineers, and IT professionals need. With a broadened scope, more emphasis on applied computing, and more than 70 chapters either new or significantly revised, the Computer Science Handbook, Second Edition is exactly the kind of reference you need. This rich collection of theory and practice fully characterizes the current state of the field and conveys the modern spirit, accomplishments, and direction of computer science. Highlights of the Second Edition: ? Coverage that reaches across all 11 subject areas of the discipline as defined in Computing Curricula 2001, now the standard taxonomy ? More than 70 chapters revised or replaced ? Emphasis on a more practical/applied approach to IT topics such as information management, net-centric computing, and human computer interaction ? More than 150 contributing authors--all recognized experts in their respective specialties ? New chapters on: cryptography computational chemistry computational astrophysics human-centered software development cognitive modeling transaction processing data compression scripting languages event-driven programming software architecture PAGE TWO-THREE
Customer Reviews:
An excellent and complete reference.......2006-07-12
This book provides a single substantive and comprehensive reference for practicing engineers and computer scientists, as well to other professional with strong computer experience and interest.
The handbook cover all mayor fields of CS&E, including algorithms and data structures, architecture, artificial intelligence and robotics, computational science, database and information retrieval, graphics, human-computer interaction, operating systems and networks, programming languages and software engineering.
An exceptional review of core CS material.......2000-12-06
I'm using this book to relearn core CS material in preparation for the CS GRE after several years in the industry. I can't recommend it highly enough.
This is not a book from which to learn concepts for the first time. If you've never heard of (e.g.) "undecidability", don't get this book intending to learn about it. However, if you know enough to know what you don't know, this book will efficiently fill in the gaps.
The book consists of over 100 chapters covering material across nearly major area of computer science. Each chapter is 20-30 pages long and is geared to someone who has seen the material before but is in need of a review and summary of core terminology and historical context. Someone experienced in one field who wants to be able to read current technical material in another field will also find it useful.
Most of the authors are academics; the remainder are members of major research labs. Some of their chapters, like James Feldman's piece on Digital Logic, are truly extraordinary. Most others range from solid to exceptional. The material isn't just that of concern to traditional academic CS; I was pleasantly surprised to see an entire section (8 chapters worth) on practical software engineering topics (development process and lifecycle models, requirements and specification, design, validation, tools, testing, project management, etc). The material was authored around 1995 or 1996, and nearly all of it is still relevant and as up-to-date as is appropriate for this sort of collection.
One minor weakness is there's no cross-chapter index or glossary. The book is organized as a collection of papers, and each paper includes its own index, bibliography, and glossary. To find material about the web, for instance, you have to hunt through the (excellent) 20-page table of contents for the relevant subsections scattered throughout. This weakness is far from fatal, however. Should the next edition add an index, it will only add value to an already exceptional collection, by making it easier to locate references to material that spans subfields.
Again, highly recommended for targeted learning.
Alot of info.....A little unreadable.......1999-05-23
There is a wealth of information in this book. Many engineers will enjoy having this reference. However, if you are not in the industry, or still a little low on the mathmatics totem pole. This book will appear to you as though it is written in Greek! It practically is with all of the differential notation. When I am finished with my CSE degree, I will try to read it again. Until then, it will stay on the shelf. Definitely NOT light reading!
Average customer rating:
- Amazing book
- Both clear and complete
- Foremost book in the field
- very useful for both beginners and experts
- Excellent applications-based approach to Error Correction
|
Error Control Coding, Second Edition
Shu Lin , and
Daniel J. Costello
Manufacturer: Prentice Hall
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Digital Communications
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Digital Communications: Fundamentals and Applications (2nd Edition)
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Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
ASIN: 0130426725 |
Book Description
A reorganized and comprehensive major revision of a classic book, this edition provides a bridge between introductory digital communications and more advanced treatment of information theory. Completely updated to cover the latest developments, it presents state-of-the-art error control techniques. Coverage of the fundamentals of coding and the applications of codes to the design of real error control systems. Contains the most recent developments of coded modulation, trellises for codes, soft-decision decoding algorithms, turbo coding for reliable data transmission and other areas. There are two new chapters on Reed-Solomon codes & concatenated coding schemes. Also contains hundreds of new and revised examples; and more than 200 illustrations of code structures, encoding and decoding circuits and error performance of many important codes and error control coding systems. Appropriate for those with minimum mathematical background as a comprehensive reference for coding theory.
Customer Reviews:
Amazing book.......2007-07-13
I have the first version of this book. Now I am so glad to have the second version too. It has great improvement. It added quite lot of recent FEC tech in, including Turbo coding, LDPC coding. Besides, it is quite easy for a engineer to understand, not awkward as some math equation filled textbooks. Its block diagram can be easily understood by an engineer like me. Amazing book!
Both clear and complete.......2007-05-15
Not only does this book contain almost all the important information about coding you could hope for, but it's written in such a clear way with such a consistent notation that it's also wonderful for learning. This book is more than twice as long as the first edition and serves as a great graduate-level text or reference for someone designing ECC systems.
Foremost book in the field.......2004-10-19
I had the previous version of this book as my text at USC. This version is a huge improvement over the last one. This one covers all the new advances and adds emphasis on the use of coding to communications channels. A complaint I had of the last version was that it under-emphasized coding gains and Eb/N0 vs. BER performance figures. This book has overcome many of those difficulties. It is still a bit ponderous in places but then it is the only book that covers the material in this much detail, truly a Bible of the field. It is a great graduate level text and a must-have book for any comm engineer. Charan Langton complextoreal.com
very useful for both beginners and experts.......1999-06-12
a very detailed book for getting into Galois field arithmetics, cyclic codes, convolutional codes, ... As a very beginner I had no big problems understanding the content. I am not the type of guy who could understand just by reading the theory - this book gives a lot of very useful examples, so you could call it fun reading it!
Excellent applications-based approach to Error Correction.......1998-10-05
Lin and Costello produced an excellent text which is targeted towards engineers as opposed to mathematicians. The mathematics behind error correction can be extremely intensive and, with other texts, I quickly become lost in complex proofs. Lin and Costello present error correction in method, with plenty of good examples, which those who need to know how to apply it can understand and the gory details of the theory are not as important. I used this book as my introduction to error correction and it continues to be a great reference book. The only drawback in it is since it was published in '82, it stops at convolutional coding and does not cover trellis-coded modulation or turbo codes.
Average customer rating:
- Accessible textbook on compression does not sacrifice rigor
- A great textbook
- Very good coverage
- "The" Definitive Guide
- Very well-written book, software not so good
|
Introduction to Data Compression, Second Edition (The Morgan Kaufmann Series in Multimedia and Information Systems)
Khalid Sayood
Manufacturer: Morgan Kaufmann
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ASIN: 1558605584 |
Amazon.com
Khalid Sayood's textbook-style Introduction to Data Compression is the definitive guide to all kinds of compression schemes. Early chapters establish the mathematics involved in basic compression techniques, including lossless and lossy compression as well as the fundamentals of information theory that lay the groundwork for common forms of compression. (The book contains all the relevant formulas, although those who don't need such mathematical detail will still be able to understand the book.)
A good portion of the book examines various compression schemes, their strengths and weaknesses, and what content they work best for. Introduction to Data Compression begins with lossless compression schemes, which lose no information during the compression/decompression process. Huffman Coding, a well-established compression scheme, and arithmetic and dictionary coding also receive excellent treatment. In addition, the author takes on lossless compression for images.
For lossy compression, Sayood discusses schemes that use quantization, where a range of values is compressed in some way. He also describes scalar, vector, and differential encoding and fractal compression. A final chapter looks at video encryption (which often combines techniques from earlier chapters). Many of the compression schemes include examples from image and sound files, but the book considers a wide variety of video schemes too. This rich and confidently written text collates a lot of research and can serve as both textbook and source for designers who need a readable and mathematically solid introduction to data compression.
Book Description
The second edition of Introduction to Data Compression builds on the features that made the first the logical choice-for practitioners who need a comprehensive guide to compression for all types of multimedia and instructors who want to equip their students with solid foundations in these increasingly important and diverse techniques.
This book provides an extensive introduction to the theory underlying today's compression techniques, with detailed, instruction for their application. All of the coverage has been updated to reflect the state of the art in data compression, including both new algorithms and older methods for which new uses are being found. And the downloadable software gives you the opportunity to see firsthand how various algorithms work, to choose and implement appropriate techniques in your own applications, and to build your own algorithms.
* Fully updated to cover the most recent lossy and lossless compression techniques, including wavelets, subband coding, predictive lossless techniques, and Huffman coding variants.
* Explains established and emerging standards in depth: JPEG 2000, JPEG-LS, MPEG 2, Group 3 and 4 Faxes, JBIG 2, ADPCM, LPC, CELP, and MELP.
* Includes an new chapter providing the mathematical background required for understanding wavelets and subband coding.
* Via the companion Web site, provides source code that enables you to experiment with a wide range of compression techniques, along with sample data and updates on the latest developments in the compression field.
Customer Reviews:
Accessible textbook on compression does not sacrifice rigor .......2007-05-19
This is one of those books that only gets a new edition when the author has something genuinely new to say, and this third edition of Sayood's excellent introduction to data compression is no exception. This particular edition is different from the second mainly in that there is a new chapter on audio compression that includes a description of the mp3 algorithm. Also there is additional information on the new video coding standards as well as the new facsimile standards.
As to the target audience for this book, if you are tasked with designing hardware or software implementations of data compression algorithms and you have some background in either electrical engineering or computer science, then this is a good book from which to learn and then to practice what you learn via some very good exercises. Some prior knowledge of information theory and random processes wouldn't hurt either. There is also an abundance of examples that are sprinkled throughout the book to illustrate concepts as they are presented. The author's approach in each chapter is to explain each concept in as an accessible manor as possible, present relevant equations, and then work an example using what has just been presented.
The book presents the mathematical preliminaries in chapter 2, and chapters 3 and 4 are dedicated to coding algorithms which include Huffman coding, arithmetic coding, Golumb-Rice codes, and Tunstall codes. Chapters 5 and 6 describe many of the popular lossless compression methods and their applications. These methods include LZW, BWT, and DMC. Chapter 7 describes various lossless image compression algorithms such as JBIG as well as their applications. Chapter 8 discusses the mathematical background of lossy compression standards. Chapters 9 and 10 concentrate on quantization since it is the basis of most lossy compression schemes. Chapter 11 discusses differential encoding techniques such as DPCM and delta modulation. Included is a discussion of the CCITT G.726 standard.
Chapter 12 is the third and final chapter dedicated to mathematical foundations. It is meant to prepare the reader for the chapters on transform, subband, and wavelet based methods that encompass the following three chapters. The JPEG standard is covered in chapter 13, the CCITT G.722 standard in chapter 14, and the EZW, SPIHT, and JPEG2000 standards are covered in chapter 15. Chapter 16 focuses on audio compression and includes descriptions of the various MPEG audio compression schemes including mp3. Chapter 17 switches gears somewhat and covers techniques in which the data to be compressed is analyzed and a model is produced. This model is then used to synthesize the data and is quite useful in speech compression. Chapter 18 deals with video compression and diverges from the book's central theme of dealing with techniques rather than applications. The chapter discusses the H.261 standard as well as MPEG-1, MPEG-2, and MPEG-4 standards.
The website for the book, found at the publisher's site, contains a large number of C programs dealing with compression. I haven't tried to use any of these yet, so I can't speak to their validity.
A great textbook.......2006-02-11
This book has all the ingredients for a great textbook. It provides good theoratical background without going into unnecessary details, gives lot of discussion about applications, provides great exercise problems, and above all it has outstanding examples that makes some of the difficult concepts easy to understand.
Data compression needs a lot of background in information theory and other areas specific to speech, image processing etc. It is impossible to give a rigourous theoratical treatment of all of those in one volume. A strong point of this book is that it gives you just enough background on a variety of topics - without making the whole book obscure. In that respect, it is very application and implementation oriented. It is in fact what it says it is: A very good "INTRODUCTION to Data Compression"
Very good coverage.......2004-12-27
The best thing about this book is the coverage and organization of the material. Sayood covers a wide variety of compression topics without getting into the nitty gritty details of them all. Thats why its an "Introductory" book. This book is a valuable resource for those who want to know the basics of various compression techniques and can be used as a starting point for further details. Some topics like arithmetic coding are covered in more detail than others. The book is also organized nicely with mathematical foundations provided as and when necessary.
"The" Definitive Guide.......2004-02-16
Amazon claims that this is "the definitive guide". I have to agree with them because this book is the only broad grey pages introduction to data compression that I have been able to find, and it is very well written.
If you are only casually interested in data compression this book is not for you.
If you are interested in adding compression to your application and your data falls into a common category, sound, video, text ect this book is probably not for you. You should look to the open source community or buy an off the shelf product.
But if your data is odd or unique like say telemtry data (I'm sure there are other examples I just can't think of any) and you need to design a compression scheme for your data this book is "the only" book for you.
If you want to begin research into data compression and you are a newbie this book is a must have.
Very well-written book, software not so good.......2003-04-25
The book is one of the clearest I have read as a text book. Why cant everybody write like this?? There is very good flow throughout the text.
Only complaint is the software. It looks the software has not kept pace with the book itself. Some additional software has to be added (for Transform coding, for instance), and some references in the text book to the software are incorrect. If the accompanying software is upgraded, as it should be, I will rate this book a clear 5-star.
Book Description
This well-accepted introduction to computational geometry is a textbook for high-level undergraduate and low-level graduate courses. The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In the second edition, besides revisions to the first edition, a number of new exercises have been added.
Customer Reviews:
Excellent Background.......2007-06-13
This book is extremely well written, easy to understand, and actually is the standard text for Computational Geometry classes, as far as I know. The only thing I didn't like about it was that there seemed to be a few errors in some of the pseudocode. But, it's to be expected when publishing a textbook, and I think it'll probably be cleared up in future editions.
Overall, great book. I'd recommend it to anyone taking graphics or a computational geometry class.
good source of many methods.......2006-02-24
The authors amass an impressive array of algorithms related to finding geometrical properties. Where these algorithms are performed on a computer. The book itself does not advocate any particular programming language. The algorithms are given in pseudocode, and you are expected to manually convert these to code in your choice of language. Given the calibre of the discussion in the text, which suggests that the readers are quite experienced, then this manual step should be easy to most.
There are numerous contexts in which the text might prove useful. Ranging from graphics to GIS to robotics. Thus, there is an entire chapter on the planning of robotic motion. The robot can in general translate and rotate.
Each chapter comes with an exercise set. Which helps make the book suitable as a graduate or even undergraduate text.
Important book but substandard layout and typesetting.......2005-12-27
This is one of the really few computational geometry books available. It fills a niche and does it decently. However it could be better:
1. The chapter layout is not very good. There are many "revisiting this" and "we saw in chapter so-and-so".
2. The mathematical proofs are often written in a single paragraph full of "English" interspersed with mathematical notation, instead of the tried and true way of numbered equations and one-per explanations. This makes for disconcerting reading.
3. The book in general could have done with more math and code, and less "English", not to mention more and better diagrams -- they tend to be sparsely detailed (ie. a picture is worth only a hundred words). The arrangement of diagrams also needs to be better: some are in the margins, some are in the middle, again not easy and intuitive to follow.
Hopefully a future edition will address this issues.
Good Introduction but look elsewhere for detailed reference.......2003-01-31
Pro:
(1) Each chapter begins with a practical example. For example, the chapter computing intersections of lines starts with a discussion of a map-making application that goes into enough detail to see how the algorithms they present would be useful. This is a considerable step up from the common practice in algorithms literature of motivation by way of vaguely mentioning some related field (i.e. "These string matching algorithms are useful in computational biology"). This book does a much better job of motivating the material it presents, but if you're primarily interested in the abstract problem, these sections can be skipped.
(2) Each chapter is relatively self-contained. Feel free to skip ahead to subjects that interest you.
(3) Surprisingly readable. Unlike most technical material, one can read an entire chapter in a single sitting without missing much. Generally, each chapter will develop a single algorithm for a single kind of problem.
(4) It's very up to date. This second edition is less than two years old, it includes some new results in the field.
Con:
(1) Algorithms are only given in pseudocode. The emphasis is on describing algorithms and data structures clearly and completely. If you're looking for a "cookbook" with code to copy and paste into an application, perhaps O'Rourke's "Computational Geometry in C" would be a better choice.
(2) There are many important advanced results that are not discussed in the main text. An obvious example is the first chapter, which describes a well-known convex hull algorithm that takes O(n log n) time but algorithms that are faster for most inputs are mentioned only in the "Notes and Comments" at the end of the chapter. Someone interested in lots of gory details would be well-served to combine this book with Boissonnat and Yvinec's more detailed and mathematical "Algorithmic Geometry".
Extremely well written.......2002-10-26
Algorithm books are often quite hard to understand, but this is not the case with this book. The information is very compact so it is a slow read but due to the high quality of the text this is only an advantage. You are never left wondering what the authors might have meant with a certain statement.
The book focuses solely on theory, so it presents no real source code (only pseudo-code) which I think is good thing since that would otherwise have polluted the clarity of the explanations.
Many of the topics it covers has been a help to me as a programmer. Can be recommended for anyone interested in computation geometry - but it requires some computer science maturity so I don't recommend it unless you have a bachelor's degree in C.S. or something similar.
Jacob Marner, M.Sc.
Book Description
This introductory text covers the key areas of computer science, including recursive function theory, formal languages, and automata. It assumes a minimal background in formal mathematics. The book is divided into five parts: Computability, Grammars and Automata, Logic, Complexity, and Unsolvability.
* Computability theory is introduced in a manner that makes maximum use of previous programming experience, including a "universal" program that takes up less than a page.
* The number of exercises included has more than tripled.
* Automata theory, computational logic, and complexity theory are presented in a flexible manner, and can be covered in a variety of different arrangements.
Customer Reviews:
Pure mathematical view of Computability and Complexity.......2002-02-14
This is not a common book on Computability and Complexity as Hopcroft-Ullman, Sipser or Papadimitrou. You won't find here too many words describing topics: you'll find the power and elegance of a superlative mathematical approach from one the best authors of the century in the field. Conversely, you'll find here a detailed and elegant treatment of the whole history of computational models that starts at the Primitive Recursive Functions, something you won't find in the other books above mentioned.
A special note goes to the chapter on Blum's complexity, which is about the only good place where I found it and from where I studied for my course on Complexity I.
For this reason the book requires quite more attention than others, but it really worths all the time one can spend reading it. Truly understanding Computability and Complexity as Professor Davis teaches them with this book is in my opinion a definitely high achievement, bringing the sensation that you grasp it totally, with no space for ambiguity or weakness.
Beautiful overview.......2001-07-11
The authors of this book define theoretical computer science as the mathematical study of models of computation, and they do an excellent job of detailing the major results in the theory of computation as related to mathematical logic. Mathematicians, programmers, and philosophers will find the book an effective one in which to learn computability theory, and it serves well as a textbook for courses in the subject.
After a brief review of elementary mathematics and mathematical logic in chapter 1, the authors move right into the consideration of computable functions in chapter 2. They choose a particular abstract programming language in which to study the computability theory, which is built from variables, and programs that can be built from lists of instructions. Examples of programs are given, which have a Fortran flavor, with examples of computing partial functions. Unfortunately, a plethora of GOTO statements appear in the programs, and throughout the rest of the book, which is surprising given the publishing date. The use of these GOTO statements in the book is a major annoyance.
Then in chapter 3, the authors discuss primitive recursive functions, beginning with a treatment of composition, followed by the all-important concept of recursion. The class (PRC) of primitive recursive functions is introduced, and shown to be computable. The primitive recursive predicates are introduced, followed by a proof that the existential and universal quantifiers over an element of a PRC class are also PRC. This is followed by a discussion of minimalization and Godel numbers.
The next chapter is very interesting, wherein the famous halting problem is discussed and related to Church's thesis. The authors stress, most importantly, that an algorithm cannot be defined outside of the choice of a language, and therefore Church's thesis cannot be proved as a theorem. The authors also introduce recursively enumerable sets and show, via diagonalization, that non-recursively enumerable sets exist. They give an interesting example of a function that is computable but not primitive recursive.
The next chapter extends the results to strings of symbols instead of just numbers, and the authors introduce programming languages for doing string computations. One of these is the famous Post-Turing language, which they use to discuss the halting problem, with a variant used in the next chapter on Turing machines. The authors discuss the famous halting problem for Turing machines in this chapter. This is followed in chapter 7 by a discussion of productions and simulation of nondeterministic Turing machines. A very lucid treatment of Post's correspondence problem is given.
Things get somewhat more complicated in chapter 8, where the authors attempt to classify unsolvable problems. It contains one of the best discussions I have seen in the literature on oracles, and the authors give a very clear treatment of arithmetic hierarchies.
The second part of the book reads more like a book on compilers, as the authors delve into the area of grammars and automata. Regular languages, deterministic and non-deterministic finite automata are discussed, and Kleene's theorem, which states that regular languages and finite automata define the same languages, is proven. The context-free languages, so familiar from the study of compilers, are discussed also, along with a proof that a context-free grammar can be reduced to a Chomsky normal form grammar. Pushdown automata, needed for accepting context-free languages, are treated in detail. The authors give a good explanation here as to the additional facilities needed for a finite automaton to decide if a word belongs to a "bracket" language. Chomsky hierarchies are also discussed, and the authors motivate nicely the need for a linear bounded automaton to accept context sensitive languages.
Part three of the book is an overview of mathematical logic, and begins with a treatment of the propositional calculus. The satisfiability problem is discussed for this system, along with how to reduce formulas to normal form. The important compactness theorem is given a very detailed proof. Predicate calculus is then discussed, and Herbrand's theorem, which effectively reduces logical inference in predicate calculus to a problem of satisfiability of universal sentences, is proven. This theorem is fascinating and has important applications to automated theorem proving, as it ties together semantic and syntactical properties of a formal system. The Godel incompleteness theorem and the unsolvability of the satisfiability problem in predicate logic is proven.
In part 4, issues in computational complexity are addressed, the measure of complexity given in terms of the Blum axioms. This is a very abstract way of introducing complexity theory, as it introduces measures of complexity that more general than time and space complexity. The fascinating gap theorem, comparing program performance on two computing machines via complexity measures, is proven. This is followed by a detailed discussion of the speedup theorem, which essentially states that there is a wildly complicated recursive function such that for any program computing this function, there exists another program computing the function that works a lot faster for almost every input. The polynomial-time computability is discussed along with the famous P vs NP problem, with the discussion given in terms of Turing machines. Examples of NP-complete problems are given.
The last part of the book covers semantics, with operational and denotational semantics defined and compared. The emphasis in this part is on programming languages and constructions that one would actually find in practice, and so the preceding chapters on computable functions must be extended. The concept of an approximate ordering is introduced to allow for the instantaneous of a computation at some point before its completion. The denotational semantics of recursion equations and infinitary data structures are discussed, with the latter put it in to deal with the sophisticated systems that are constructed here. The discussion here is very involved, but the authors do a fair job of explaining the need for these types of data structures. The same is done for operational semantics, and the authors finally show that the computable numerical functions are actually partially computable. They then show the existence of computable irrational numbers.
My favorite book on the theory of computation.......2000-05-11
I first learned computability from this book and I loved every minute of it. It has lots of material and is superbly written. In fact, I think the chapters on logic are the most painless way to learn that subject. There are many other books around on this subject, but this is the ultimate!
CS Theory at it's best.......2000-03-30
I haven't found a better book on the Theoretical foundations of Computer Science. However since this IS theory the text can be a bit cryptic. Still, I'd recomend this book to any PhD Candidate or full Professor. Even a lowly Master's student like myself could use it.
This is a wonderful text about the theory of computation........1999-02-25
It taught me how to think about the theory of computation. The exercises added to the second edition are a big improvement over the first editon.
Product Description
There is no other information retrieval/search book where the heart is the mathematical foundations. This book is greatly needed to further establish information retrieval as a serious academic, as well as practical and industrial, area." ---Jaime Carbonell, Carnegie Mellon University. Berry and Browne describe most of what you need to know to design your own search engine. Their strength is the description of the solid mathematical underpinnings at a level that is understandable to competent engineering undergraduates, perhaps with a bit of instructor guidance. They discuss the algorithms used by most commercial search engines, so you may find your use of Google and its kind becomes more effective, too. --George Corliss, Marquette University. This book gives a valuable, generally non-technical, insight into how search engines work, how to improve the users' success in Information Retrieval (IR), and an in-depth analysis of a mathematical algorithm for improving a search engine's performance.
Written in an informal style, the book is easy to read and is a good introduction on how search engines operate
Christopher Dean, Mathematics Today, October 1999. The second edition of Understanding Search Engines: Mathematical Modeling and Text Retrieval follows the basic premise of the first edition by discussing many of the key design issues for building search engines and emphasizing the important role that applied mathematics can play in improving information retrieval. The authors discuss important data structures, algorithms, and software as well as user-centered issues such as interfaces, manual indexing, and document preparation. Readers will find that the second edition includes significant changes that bring the text up to date on current information retrieval methods. For example, the authors have added a completely new chapter on link-structure algorithms used in search engines such as Google, and the chapter on user interface has been rewritten to specifically focus on search engine usability. To reflect updates in the literature on information retrieval, the authors have added new recommendations for further reading and expanded the bibliography. In addition, the index has been updated and streamlined to make it more reader friendly. Instructors will find that the book serves as an excellent companion text for courses in information retrieval, applied linear algebra, and scientific computing. Because of the authors informal, conversational tone, readers with nonmathematical backgrounds also will appreciate the less technical chapters of the text.
Customer Reviews:
Good Introduction.......2007-05-07
There are better books in the market, and even the author would be the first to recognize it. However, this book is one of the most clear and readable introduction to the subject that you can find.
The author fully acomplishes the objective: teach his reader, at undergratuate level, how search engines work. Even some difficult subject, such as LSI, are treated at a level one can easilly understand.
One of the most important characteristics of the book is that it does math. Every formula has an example, usually using small matrix that allow the reader to easilly follow them.
The book is suitable for an objective introduction to the field. It is not very "academic", in the sense it is rather informal. If it is not a textbook, it could help some bewildered student to grasp the inner workings. It could also help a teacher to find clearer ways for explanations and good examples for classroom.
Read at the bookstore, no need to buy.......2002-05-19
This little booklet is best to be read at the bookstore.
There is no need to buy. In fact, buying it is a waste
of money, given the $[money] price tag. That is about a $[money]
a page.
So, save your money and time...
Appreciations from a novice........2000-06-29
I read this book because I am starting academic research on search engines. It was one of my first books on the subject. It actually deals with two aspects: (1) relevant issues in search engine design, and (2) a mathematically sound approach in building and querying large index strucutres. The explanation in the book on both aspects is short but to the point and explained in an understandable way. It also contains a short list + description of some key references. Great !
Average customer rating:
- Second Review of Dr. Hein's Book
- Excellent book!
- This book is not very good.
- A Good Text
- Discrete math for real software engineers
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Discrete Structures, Logic, and Computability, Second Edition (Jones & Bartlett Computer Science)
HeinfJamesL
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ASIN: 0763718432 |
Book Description
This book introduces the beginning computer science student to some of the fundamental ideas and techniques used by computer scientists today, focusing on discrete structures, logic, and computability.
Customer Reviews:
Second Review of Dr. Hein's Book.......2004-07-16
Now, since I took two terms of classes that used Dr. Hein's book, I had internal urges to write emails to Dr. Hein and praise him for his book and his lab manual (but I never did wrote to him, though). Instead, I decided to write to a broader audience, here at Amazon. I found the book ABSOLUTELY NECESSARY, a Holistic Bible of Computer Logic so to speak, for every CS student. I have read and re-read the book and still reading it today, during the Summer Break. I scanned the whole book with a flatbed scanner because I needed to look things up often even as I studied other courses at Portland State University. I also highly recommend Dr. Hein's Prolog Lab Manual which guides you through the experiments designed to help understanding the Book's material. Marvelous Lab Manual, Dr. Hein! It is my opinion that Doctor Hein has a profound vision of where Computer Science is going and that's why he designed his Book and his lab manual this way. The Book and Lab Manual helped me tremendously to understand recursion and logic.
PS: I never write reviews of books, but this particular book have always prompted urges to praise it.
Excellent book!.......2003-08-27
This is an excellent book! Easy to read and understand. I am an "A" student, at Portland State University and I think that people who wrote bad reviewes of this book did not read the book (just like they might read every 50th page of any other book). Bill Gates once said that every person is born to be able to understand only up to a certain level of abstraction. Just like some of us are born to be able to lift 500 lbs. and some only 50 lbs. In addition, a person has to have some background to be able to understand more advanced topics. The book is most excellent.
This book is not very good........2002-12-14
This book makes a better door stop, than a academic text book. Having taken the classes at PSU I know this book front to back. The dosent really explain the subjects well, the book as a whole lacks focus. The first half of the book is horribly written, and abismal when actually compated to a discrete mathmatics, and/or group theory book. So much so there is a bit of a running joke about it in the math department. I would recomend to any CS student to avoid the text book and study from a regular math book instead.
A Good Text.......2002-01-03
I've taught from this text for 8 years. The excellent students have no problem with it. The average students complain that it is hard to understand. I don't think any text covering these topics could be easier to understand, actually.
There are plenty of examples in the text. However, the exercises tend to be significantly more complex than the examples. The answers to many exercises are in the back of the book, which is a great help to students.
Discrete math for real software engineers.......2000-04-06
Software designs must address trade-offs among factors such as performance, usability, completeness, timeliness, correctness and so on. Judging from the number of bugs people encounter, software engineers seem to be trading away too much of the correctness factor for something else.
Hein's text addresses this issue by placing much greater emphasis on ideas from logic and methods of proof than most other books on discrete mathematics, such as the popular text by Rosen. In addition, Hein includes material relating important software concepts to abstract algebra, and he does this without slighting other common topics of discrete mathematics, such as sets, relations, functions, counting, automata, and computability. Software engineers who have learned from Hein's text will have practical tools that they can use to deal with the software correctness factor more effectively.
Besides all of these good qualities, the text is well organized, clearly written, and punctuated with deligtfully subtle humor. I plan to use it.
Book Description
This new edition of Jerry D. Moore's Visions of Culture presents introductory anthropology students with a brief, readable, and balanced treatment of theoretical developments in the field. New to this edition are pieces on Sherry Ortner, Pierre Bourdieu and Eric Wolf, an Epilogue that describes key current debates over theory. This is an ideal text for classes on the theory or the history of anthropology.
Customer Reviews:
A must!.......2007-09-20
This was first required as an undergrad for a theory class. It has become a wonderful refrence that I use often as a graduate student. It is clear, presise, organized, and to the point on all the major theorists of anthropology. Whenever I forget who did what, or what major contribution someone made, this is a wonderful refrence! My only suggestion: I wish they would publish a new edition to include more "modern" theorists.
Any Anthropology student should have..........2003-06-10
"Visions of Culture" is an essential book for any student of anthropology. It would be wrong to consider this book a textbook though. It is more of a reference on specific theorists. What Moore does is to write concise, informative chapters on each of the major anthropological theorists. He begins with biographical data, and goes on to discuss their theories. It is an indispensible reference for the student of culture. I reference it more than any other individual anthropology book.
Amazon.com
Software developers make their programs ever more graphical; interfaces become ever more slick. But underneath the buttons and sliders, PCs are electronic systems comprising power supplies, logic processors, and specialized circuitry for such functions as video and sound. When the machine grinds to a halt, someone has to know how to identify the problem and get it straightened out. That's the function of the CompTIA A+ certification, and this new edition of Mike Meyers' A+ Certification Passport will help you earn it. Meyers combines reams of detailed information about IBM-standard PCs (which is to say, those running Intel, AMD, and Cyrix) with rock-solid troubleshooting advice. Look here for electronic details of the IDE and SCSI interfaces, as well as strategies for figuring out whether a problem is in a drive or in its controlling electronics.
Meyers has organized his book around the two A+ exams, which means you'll find excellent coverage of the subjects CompTIA includes (hardware from early days through the Pentium III era, and Microsoft MS-DOS and Windows operating systems through Windows 2000). Inversely, you'll find no coverage of potentially useful subjects that CompTIA doesn't test (Linux and Microsoft Windows XP, most notably). Updated coverage--of new USB and FireWire standards, as well as memory specifications--meets the high standard of the previous edition. This book will help you prepare for the A+ exams; it and a couple of supplementary texts will get you ready for the job site. --David Wall
Topics covered: The electronics of IBM-standard personal computers (motherboards, processors, memory, disk drives, video cards, network interfaces, and so on), and strategies for safely and efficiently troubleshooting and repairing them. Later chapters explain how to do configuration work in Microsoft MS-DOS, Windows 95/98, Windows NT, and Windows 2000 Professional.
Book Description
Mike Meyers, the industry expert on professional certification, brings you this concise, affordable, and portable study tool for the A+ certification exam. With an intensive focus on only what you need to know to pass this challenging exam plus practice exam software on CD, this Certification Passport is your ticket to success on exam day.
Customer Reviews:
"A+ Certified!!".......2007-10-05
All hail the "Alpha Geek" Mike Meyers!! I took the A+ Hardware exam in September 2006 and the OS Technologies exam in April 2007 and passed both easily using this Passport book and Mike Meyer's bigger book the "All In One A+ Certification" Guide. Everything that is written in the Passport book will be covered on the exam. Read through the whole book carefully about two times and you will do just fine. I've been doing hardware/software support now for about 5 years, and even I've learned some new things thanks to the help of Mike Meyer's book. If you are very new to hardware or software, I would recommend getting some hands-on experience in addition to reading the material. Do some volunteer work at your local charity/non-profit organization. Offer to help your friends or neighbors with their computing problems. You won't believe how much more proficient you will become the more you actually do it. Practice does make perfect, especially when dealing with hardware and software issues. Good luck to everyone pursuing the A+ Certification. :)
Don't bother reading the reviews, they are for the old book........2007-08-22
Amazon has all the old pre 3rd edition reviews posted. These reviews are for the old books and the old exams.
It's OK.......2007-08-09
I wish people would take the tests before rating these books.
My scores are 810/900 and 840/900 for Essentials and 602 respectively. Passing scores are 675 and 700 with 100 being the minimum.
I bought this book and A+ Certification All-in-One Exam Guide, Sixth Edition (A+ Certification All in One Exam) by the same author. I also bought the exam vouchers from them which came with 300 practice questions. Both books come with practice questions both in the books and additional ones on the accompanying CDs. However, the CDs and the downloaded questions were mostly repeats and nothing like the actual exams (same goes for the books).
I have over twenty years of tinkering with computers. I was an aerospace engineer and an Oracle database programmer. I just wanted to get this Certification for kicks. There is a lot of fluff in both books which has nothing to do with the exams. Neither book really tells you how the actual exam questions are like. Actual exams are generally much simpler and test you mostly on your broad knowledge rather than the fine details (the exams does not ask which socket Pentium II uses, but it does ask what does a series of long beeps mean after you boot up). If you know the basics and understand the logic, you will pass. You still need to know some details, but they are not the hard ones. There has to be better book out there.
Even though I already knew 80% of the subject matter, I studied real hard. There is more stuff in the other book worth knowing though (not for the test). But personally, fluff puts me to sleep. Just keep it brief and to the point and pertinent to the test, that's what the books are selling.
If you buy these books, make sure you already have some experience in the field and that you really study these books like a text book.
GREAT BOOK!.......2007-01-25
I PASSED WITH ONLY THIS BOOK!, THE A+ SERIES FROM MIKE MEYER'S ARE THE BEST!
Good book, but too many errors.......2006-09-23
I just passed my A+ tests; both in the 700 range, so I have to give Mike Meyers kudos for a really good book. The reason I gave this book 3 stars though is because there were too many errors in it. Words used that shouldn't have been used, sentences that made no sense, figures that were misnumbered, etc. I also used the 1100 A+ questions and those were also screwed up. One question said that ME can use NTFS. I emailed Mike Meyers about the book and he blamed the publisher for all the mistakes in the book. I've heard that other authors and publishers are just as bad so I guess we don't have much of a choice here. I did pass the tests so
even with all the mistakes, I am getting his Network+ book since it was rated so high. There really is no excuse for all the mistakes in books like these. In chapter 17 you will see "An NIC" instead of "A NIC" over and over again. That is just one out of many mistakes. I don't know how that could be the publisher's fault but I'll give Mike Meyers the benefit of the doubt.
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