Probability and Computing: Randomized Algorithms and Probabilistic Analysis

Book Description

Assuming only an elementary background in discrete mathematics, this textbook is an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It includes random sampling, expectations, Markov's and Chevyshev's inequalities, Chernoff bounds, balls and bins models, the probabilistic method, Markov chains, MCMC, martingales, entropy, and other topics. The book is designed to accompany a one- or two-semester course for graduate students in computer science and applied mathematics.

Customer Reviews:

Advanced probability topics without measure theory.......2007-08-18

This book is underestimated by two reviewers below. I totally do not agree with them. This book covers a wide range of topics in a very readable style. The contents in this book is complementary to the book of Motwani and Raghavan (but this book is much easier to digest).

It, without requiring any knowledge on measure theory, contains excellent introductions to many difficult topics in probability including

- concentration bounds (Chernoff, Azuma-Hoeffding, etc.)
- applications of stochastic processes such as queuing theory
- martingale (Wald's equation)
- coupling of Markov chains and their mixing times
- Shannon's source coding and noisy channel theorems
- Erdos' probabilistic method
- etc.

All of these topics are provided with excellent applications in computing.
The authors illustrate many clever tricks for proving theorems, and these tricks give insights to the readers as well.

Just unnecessary.......2007-05-17

This book, while written by two renowned computer scientists, is truly disappointing. In trying to discuss randomness and computation, this book just does a mediocre job on discussing randomized computation and also an equally poor job discussing relevant aspects of probability theory. Their approach is not novel and many of their examples can be found in other texts. If you really want to learn randomized computation, get Motwani et al's book on Randomized Algorithms. If you want to learn probability theory, get any advanced probability theory book like Spencer and Alon on the probabilistic method, one of Sheldon Ross's books, or even Grimmett and Stirzaker. Whatever you do don't get this weak hybrid of a book that will require you to get another book at some point to supplement your understanding.

Another poorly written text book.......2006-03-19

The authors must be smart guys. They obviously understand alot about this subject but make the mistake that you do too! As a result, the book is inadequate as a teaching tool.

They use only half to a third of the narrative they need to adequately explain a subject. They also like to leave out proof steps or not explain them. The problems at the end of chapters are poor as well, since the authors seem to have forgotten to teach the techniques needed to solve most them in the chapter they belong to.

I am sure to them it is intuitive.

Good Introductory Textbook.......2005-03-16

It's pretty easy to get computers to do things where the answer is yes or no, or 4 or 6, given that the inputs to the problem are known. It's much harder to get an answer to a problem where the answer is that their is a 62% chance that the answer is yes. Unfortunately, in real life it's this second class of problems that predominates.

This book is oriented to solving these kinds of real world problems. The exercises in the book are chosen from real world examples -- what we used to call story problems. This tends to give the student a better understanding of not only the mathematics and programming involved but experience in looking at problems with a view to understanding this approach to solving the problem.

This book is suitable for a one or two semester introductory class at the upper undergraduate or beginning graduate level.

Just a word about the illustration on the front of the book. At the end of the book Alice in Wonderland the queen is about to order Alice beheaded. Alice says, "You're nothing but a pack of cards." At this, the whole pack rose up into the air and came flying down around her. This illustration is by John Tenniel from the original book of 1899. A deck of flying playing cards is a good way to illustrate random and probability.

Average customer rating:

very nice conceptual overview
Not for the practitioner
Trash
Excellent Introduction, Sparse on Details
A Good Introductory Survey

Scientific Computing
Michael T. Heath
Manufacturer: The McGraw-Hill Companies, Inc.
ProductGroup: Book
Binding: Hardcover

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ASIN: 0072399104

Book Description

Heath 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators. The treatment is comprehensive yet concise, software-oriented yet compatible with a variety of software packages and programming languages. The book features more than 160 examples, 500 review questions, 240 exercises, and 200 computer problems. Changes for the second edition include: expanded motivational discussions and examples; formal statements of all major algorithms; expanded discussions of existence, uniqueness, and conditioning for each type of problem so that students can recognize "good" and "bad" problem formulations and understand the corresponding quality of results produced; and expanded coverage of several topics, particularly eigenvalues and constrained optimization. The book contains a wealth of material and can be used in a variety of one- or two-term courses in computer science, mathematics, or engineering. Its comprehensiveness and modern perspective, as well as the software pointers provided, also make it a highly useful reference for practicing professionals who need to solve computational problems.

Customer Reviews:

very nice conceptual overview.......2006-07-22

Wow, people seem to be really split on this book. I had Mike Heath for numerical analysis/scientific computing and he was an excellent instructor, one of the best lecturers I've ever had. (As a consequence, I have a hard time separating the book and the class, so judge accordingly.) The book is based on his lecture notes, though he added some material and didn't cover every topic in the book. Just reading the book is useful to give you an overview of the point behind different methods. The goal of the class for which this book was written is actually quite conceptual. It was to give scientists (that's me: a stats researcher who makes heavy use of numerical computation) and CS people in areas other than scientific computing a leg up. It was only a first class for people in scientific computing, the rough equivalent of intro Physics or intro Probability/Stats for people in those respective majors. However, you *won't* be prepared to "roll your own" from this book. In fact, at the beginning of the semester Heath was very careful to note that if you have the opportunity to use a library function for most numerical programming, you are nuts to roll your own. Why? Numerical algorithms are usually extremely complicated and the authors of the code often spend years developing careful expertise on them. Frequently the formulas used to elucidate a given method are NOT the ones used to implement it. You need error traps, tricks to handle ill-scaling and other special cases, etc. These are things that someone who has a one-semester, superficial understanding of a topic simply won't have. So consider the book on the goals it set: it is an overview of a field. If you want to learn more about any one topic, you have to dig deeper and consult references and other works, but this is a good place to start. For this, the book serves admirably.

Not for the practitioner.......2005-11-17

If you are interested in Scientific computing from the viewpoint of the end user that is the guy who uses the method to solve practical engineering problems then this book is lacking.

Not enough methods in this book to constitute an introductory survey of the field. Every chapter gets heavy dose mathematical treatment, apparently Heath loves his math but for the rest of us it doesnt translate into know-how. Know how to solve equations using computational techniques. Very few derivations to back his mathematical swagger, very few examples (if any) and fewer numerical schemes to solve problems. Many of the chapters receive cursory treatment such as PDE's get about 70 pages of print. Far too little to do anyone any good.

He does talk about interesting issues such as conditioning and error analysis and computer precision and memory issues but it is done from such a superficial viewpoint that one cannot use anything to improve ones code. Not recommended if you want to learn numerical methods even if you have an excellent professor to learn from. His chapter on FFT's was even more abstruse and there was hardly any methods with which to solve PDE's.

I had this for a graduate course in Numerical Methods but ended up using Hoffman's excellent book on Numerical Methods.

Trash.......2005-10-14

If you want to have a solid understanding of numerical computation, this book is definitely the last choice. Many theorems are given without any proof or even intuitions behind them in this book. Even when a proof is provided, it's often far from rigorous. The organization of chapters is the worst I have ever seen, revelant materials are scattered over several different locations rather than put together. Take the SVD for example, it is mentioned in the end of chapter 3, but reappears in chapter 4, which is very confusing. If you are new to this area, please don't read this book. It gives you many many facts without explanations, which I think is not a good way to learn new things. David S. Watkins' Fundamentals of Matrix Computations is a lot better and easier to understand. It also emcompasses many detailed treatments of various theorems. If you have bought Heath's book, don't be sad, at least it can serve as a coaster.

Excellent Introduction, Sparse on Details.......2004-11-20

While sparse on the details of many of the algorithms and theorems mentioned, as an introduction it covers a broad range of material-enough for two semesters of study. The writing is lucid, and when a proof of a theorem is given, it is easy to follow and explained in english afterward. Rationale is given for everything, which is a great benefit to a student not familiar with the nuances of sophisticated linear algebra.

A Good Introductory Survey.......2002-11-05

This book excels at presenting a reader with little to no knowledge in computer science and a mild mathematical background (knowledge of differential equations as a prerequisite) with the fundamental concepts regarding scientific computing. The presentation of pseudo-code algorithms helps smooth the transition from analytical (pencil and paper) thinking to numerical thinking. The algorithms are presented in a manner such tha anyone with access to dozens of possible environments can apply them, though they are by no means complete, thus requiring some thought into the processes. The material covered is 110% of what an engineer will want to know, 90% of what an applied mathematician will want to know, and 45% of what a numerical analyist will want to know. In all, a great book to begin a foray into numerical computing.

A Wavelet Tour of Signal Processing, Second Edition (Wavelet Analysis & Its Applications)

Average customer rating:

Great Book
The most universal treatment of the subject
The worst textbook I have ever seen
Algorithms and much more!
A bold approach to wavelet transforms that simplifies

A Wavelet Tour of Signal Processing, Second Edition (Wavelet Analysis & Its Applications)
Stéphane Mallat
Manufacturer: Academic Press
ProductGroup: Book
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ASIN: 012466606X

Book Description

This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and École
Polytechnique in Paris.

Key Features
* Provides a broad perspective on the principles and applications of transient signal processing with wavelets
* Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms
* Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection,
multifractal analysis, and time-varying frequency measurements
* Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet
* Content is accessible on several level of complexity, depending on the individual reader's needs
New to the Second Edition
* Optical flow calculation and video compression algorithms
* Image models with bounded variation functions
* Bayes and Minimax theories for signal estimation
* 200 pages rewritten and most illustrations redrawn
* More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics

Customer Reviews:

Great Book.......2007-03-20

A great tool for Harmonic Analysis. The book is really well written, a most read for any one who is interested in the area of wavelets, S.P. or harmonic analysis.

The most universal treatment of the subject.......2005-06-08

I say universal because this book would appeal to engineers, computer scientists, and mathematicians alike. Mallat was particularly successful to present the topic in a sufficiently rigorous way but without losing sight of the practical and more intuitive side. The presentation comprises the mathematical and the signal processing viewpoints simultaneously. The wavelet field is very vast by now with several subfields. In this respect, Mallat made a great selection of topics in this book. There is a chapter on estimation which offers great review material and pretty much the state-of-the art on signal estimation over a wavelet basis. The chapter on approximation is particularly useful for those who are not well versed in approximation theory and thus are unable to understand other treatments. If you're interested in learning wavelet theory to solve practical problems such as image compression, signal estimation, etc, this is the book to have.

The worst textbook I have ever seen.......2004-02-12

I just finished Chapter 3 of this book, but I have had enough of it. Conceptions about Fourier Transform are not clear at all. And the most unbearable thing is that, there are many printing errors which may lead to misunderstanding.

Algorithms and much more!.......2002-07-10

The subject of wavelets has many facets, --infinite in all directions;-- some of the more exciting sides of the subject
are algorithmic, and the underlying mathematical principles are both simple and powerful. Stephane Mallat's great, and readable, book, in both of its editions, brings
this out wonderfully!

A bold approach to wavelet transforms that simplifies.......2002-04-24

This is an outstanding tour through the field of wavelet decompositions of both continuous and discrete signals. It employs the formalism of Hilbert space, instead of linear algebra. This is important because the power of this formalism yields insights into the subject matter that are practically impossible in linear algebra. The formalized approach allows a wide variety of subjects to be placed on a common basis (no pun intended). For example, the transition of the treatment of the Fourier transform into Hilbert space, brings to bear the powerful guns of that space (such guns as inner product and completeness), and allows for a truly elegant proof of the Parseval and Plancherel formulas.
Parseval's theorem, simply stated, is that the inner products in Hilbert space are conserved by the Fourier transform. How simple. Linear algebra approaches cannot hope to make things this simple.

Proof of the General Sampling Theorem is equally elegant; it is shown that the projection of the function to be decomposed onto a basis function gives the discrete spectral coefficient.

Readers will also enjoy the treatment of windowed Fourier transforms and frames.

I should add a note about the style of the treatise. This treatise is not ordinary. It consistently uses very precise and carefully defined symbology. Contrary to popular belief, this makes the text easier to read, not more difficult. Once the reader understands the symbol set being used (they are all defined in the front of the text), even the proofs are tractable. Yes, I said proofs. That is another aspect of the text. There are proofs embedded in the text, without loss of continuity or clarity. Proofs are necessary to a good understanding of the subject matter. The formalism of theorems, lemmas and propositions makes the conclusions understandable, because the theorems, lemmas and propositions supporting the conclusions are identifiable.

I applaud the author for his approach and recommend that other text book writers use the same approach.

Network Flows: Theory, Algorithms, and Applications

Average customer rating:

the best network flow book for computer scientists
Good Introductory Book
Great book for Network Theory and Application
Great book for Network Theory and Application
PLEASE, write a corrected edition!

Network Flows: Theory, Algorithms, and Applications
Ravindra K. Ahuja , Thomas L. Magnanti , and James B. Orlin
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

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ASIN: 013617549X

Book Description

Bringing together the classic and the contemporary aspects of the field, this comprehensive introduction to network flows provides an integrative view of theory, algorithms, and applications. It offers in-depth and self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including a description of new and novel polynomial-time algorithms for these core models. For professionals working with network flows, optimization, and network programming.

Customer Reviews:

the best network flow book for computer scientists.......2004-12-18

I've been using this book as the primary text for my class in
"Network Flow Programming" (senior & graduate level) at the
University of Tennessee for about 10 years. Prior to that time
I had used Jensen & Barnes' Network Flow Programming (now long out
of print). The code in Jensen & Barnes is in FORTRAN (not so fun
or useful for CS majors) and the intended audience seemed to be OR.
Ahuja's code is pascal pseudo-code for the most part, which usually
translates easily into the C language that most of our students
use.

For CS students, there is excellent use of algorithm analysis
(big-O) throughout the book, and there are long discussions
about different approaches and algorithms and the complexity of
each. There is a lot of mathematical notation, but my students
have never had to worry about PDEs and the like here. Any good
advanced CS student (graduate or undergraduate) will find the
book very worthwhile. In my course the students must implement
min-cost spanning trees, shortest paths, critical path/PERT
networks (not in Ahuja), max flow, and min-cost flow. I would
also recommend (for CS majors) Tarjan's excellent (and
succinct) Data Structures and Network Algorithms.

Good Introductory Book .......2004-12-13

This is a good introductory book. I particularly liked the applications of the problems, introduced in the book. The main negative point that I could mention is, the redundant explanations and discussions you might see in different chapters. I would say the volume of the book could have been reduced by some 15%-20%, if the authors had chosen to be more concise.
The book, Combinatorial Optimization by William J. Cook, et al, is an alternative. It covers a whole lot of topics and is just too succinct, a little more elaboration would have been appreciated !

Great book for Network Theory and Application.......2003-09-25

This book contains a lot of great algorithms for network flow theory and it also contains many of the great applications, which are very useful in practice. This book is very completed. Personally, I learn a lot of new things about Multi commodity Flow, which are the use of Lagrangian Relaxation, Column generation, Resource allocation techniques for solving multi commodity flow. There are also the good chapters in Convex cost flow and Generalized Flow and good appendix in complexity. Beside this book is very easy to read and understand. It is a great idea to have if you are in OR or IE major. :)

Great book for Network Theory and Application.......2002-08-01

PLEASE, write a corrected edition!.......2002-02-28

First of all, I am not surprised that the book
got so many good reviews: at first look, it is truly
impressive, and it is clearly a work of love. I was
looking forward to teaching from it.

It is quite clear from the reviews though, that the
reviewers have not **used** it for teaching; they may
have browsed it at most.

The first disappointments came very soon in the course I
taught. The biggest flaw of the book is the really bad style
in which the proofs are written. They manage to be seemingly
overflowing with explanation, and at the same time difficult
to understand. They gloss over many details: if the teacher
tries to skip these, an alert student could easily make
him/her look pretty silly.

One case in point is the proof of the label correcting
algorithm's correctness starting on page 136. I knew this
material from before, so I thought preparing class from
here would be a breeze. I was wrong: after going back to
my notes, and breaking up the mess into several simple
claims did I manage to make notes from which I could teach.
Whoever missed the class was helpless, when they looked
for explanation in the book.

I only remark, that all classes that I taught from this book
were at some of the top 10 OR depts at the US... so this is
hardly the students' fault.

Many exercises are wrong as well, and although the authors
claim that they will try to fix the mistakes, they hardly ever
reply to reader's comments, as some of my fellow professors
told me.

I can only compare the style of the exposition to the
later written Combinatorial Optimization book by
Cunningham et. al. There is a WORLD of difference.
One can try to look up for instance, the proof
for the label correcting algorithm: the proof in the
Ahuja et. al book is practically creaking at the joints,
while in Cunningham et. al. it flows lucidly.
I suspect that the authors of the latter book wrote it, since
they were unhappy with this one; one can hardly be surprised.

On the positive side, the plethora of applications presented
is truly amazing, and the exercises (when correct) are excellent.

To sum it up: A good book, which could have become a great one,
but have not; one which is very useful, but at the
same time very hard to use... I think the community would thank
the authors for a second, revised edition, that would fix
all the mistakes, and all those terrible proofs.

Book Description

This book offers guided access to a collection of algorithms for the digital manipulation and analysis of images. Written in classic "cookbook" style, it reflects the authors' long experience as users and developers of image analysis algorithms and software. For each task, they present a description and implementation of the most suitable procedure in easy-to-use form. The algorithms range from the simplest steps to advanced functions not commonly available for Windows users. Each self-contained section treats a single operation (histogram evaluation, low-pass filtering, and edge detection, among others). The coverage includes typical situations requiring that operation and then discusses the algorithm and implementation. Sections start with a header illustrating the nature of the procedure through a "before" and "after" pictorial example and a ready-reference that lists typical applications, keywords, and related procedures. Annotated references can be found at the end of each section. An accompanying CD-ROM contains a collection of C programs for carrying out the book's procedures.

Customer Reviews:

More of a toolbox than a textbook.......2007-04-07

I already knew image processing when I bought this book, so I am not sure how it would appear to the novice seeking a textbook on the subject of image processing and analysis, but I imagine it could be somewhat confusing. I always recommend Gonzales and Wood's "Digital Image Processing" for those seeking a clear read on image processing and analysis from the ground up. Where Seul's book comes in is with clear descriptions and working code for many basic - and some not so basic - image processing and image analysis algorithms. The book is also very good at explaining the applications of the various transforms. One of the little things that the author of this book does that authors of other books similar to it don't bother to do is to realize that when you are working in image processing you likely have an image as an input and you want an image as an output. Thus the author has built his code libraries so that they work that way. You are not left with arrays of pixels that you have to figure out how to store and manage. In the end you have a nice functional toolbox of working image processing and analysis subroutines that you can chain together and make just about any type of image transform tool you could think of. I'm mainly interested in image effects, and I know this book has been useful to me. The accompanying CD-ROM contains all of the C source code for the algorithms so that you can port them to another language or tinker with them if you so desire. Highly recommended.

Good handbook for practitioners.......2007-01-30

The title of this book corresponds to its content, the tutorial gives an excellent overview of basic key points to those readers who are unfamiliar with the subject (as I was). The book can not be used for rigorous study of even simple things but rather kicks you with essentials that are easy to understand with high-school background. This book, written for non-specialists in "image field", gives them techniques for their practical needs and concentrates exactly on image analysis, not on image processing. If you have no time to go through more complex (and deeper) books, take this one to discover basic principles in short form with no attempt to explain the fundamentals. The authors just put you into the facts, so that is why I would characterize the "Practical Algorithms" book as being "handbook". The good point is that the areas of applicability of these facts are explained, the drawback: you have to go to other books to get more details on image processing roots, e. g., to R. Gonzalez and R. Woods' "Digital Image Processing". I bought both, and use them as good annex to each other. The "Practical Algorithms" has lack of some significant areas, like snake algorithm and image binarization (thresholding) techniques but e.g., the cellular processing is quite well highlighted.
Surprisingly, the CD that comes along with this book gave me almost 80% examples that I was able to recompile instantly, and only several examples have failed, mainly due to image file format issues. The source code is not both elegant and bugless, but it is very transparent and portable and can easily fit, e.g., a 16-bit microcontroller.
Overall, this is good book for fast start. You can get real output and pick up ideas on practical side of image analysis. Just remember, the most book examples came from the medicine world, so they are quite specific and may not be implemented directly in your particular application.

Image Analysis Book Review.......2004-12-06

I found the book to be very informative and I acquired several ideas from reading it. But, I repeatedly found myself searching the book for definitions of some of the terms it uses throughout its text. Practical Algorithms for Image Analysis will introduce new terms without any hint of their meaning, assuming that the reader already knows all they need to know about the subject matter (which would negate the need to buy the book!). This book sorely needs a glossary.

It's just great.......2002-10-15

The book is just great! I used the source code from the CD-ROM for various image processing projects. The algorithms are also very practical if you have to deal with images. The code is neat and ready to compile and run.

Also this book is good on the description of image process and image analysis algorithms. I read the whole book and use it as a reference during my programming. It sits in my bookshelf and I use it almost everyday.

I recommend anybody who wishes to do serious image programming to have this book. It's just great!

Luis J Gutierrez.......2001-04-22

Excelente libro. hace un tiempo que he estado estudiando y desarrollando estrategias para la implementación de sistemas de vision computarizada. Este libro es de una gran claridad práctica sin abandonar la necesaria base teorica. Muy buenos ejemplo, información adicional, ejemplos y aplicaciones. Para cualquier investigador en el área debe ser considerado como un recurso indispensable. (if you want my comments in english please send me an e-mail to innovacl@vtr.net)

Combinatorics: Topics, Techniques, Algorithms

Average customer rating:

Excellent textbook for researchers
Sigmas all over the place
Excellent book...very clear, well-organized
Great book for Computer Scientist
Very helpful

Combinatorics: Topics, Techniques, Algorithms
Peter J. Cameron
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0521457610

Book Description

Including many algorithms described in simple terms, this book stresses common techniques (such as generating functions and recursive construction) that underlie the great variety of subject matter.

Customer Reviews:

Excellent textbook for researchers.......2007-10-02

The book is an excellent source of combinatorial insights and techniques for researchers, especially those who are not mathematicians. The book is comprehensive but not too dense. Puritans would complain that it skips details, but details can always be found by referring the bibliography. An excellent source of problems, with solutions for earlier versions provided by the author on his web-page. Should turn out to be a classic if not already one.

Sigmas all over the place.......2007-03-31

This isn't your usual "urn-has-3-red-balls-and-5-white-balls" sort of combinatorics book. It's sigma notation all over the place, if you know what I mean.
The first part can be used for undergraduates and the second part is more advanced. The book is broad in scope because, as the author explains, so is the subject matter.
The chapters have "techniques" and "algorithms." It's not a book that has a slew of examples of combinatorial problems (like so many), but leans toward mathematical sophistication in formalizing the techniques. This is either a feature or a bug, depending on what you needs are. For instance, it's not very often that introductory books present derrangements next to Fibonacci numbers. Or explain how calculate the average number of comparisons that Hoare's Quicksort does with a differential equation for the recurrence relation in the context of finite fields. It sounds scary, I know, but if you look at the explanation, you'll see you should have been born a nephew to this author.
In case you like Knuth's Concrete Mathematics you will like this book too (there's some overlap, because both are concerned with the analysis of algorithms). Knuth's book works more on skill-building, and I think Cameron's book is better for theoretical explanation.
Disclaimer: I haven't worked with the whole book (because of a lack of time - "Ars long, vita brevis", as they say).

Excellent book...very clear, well-organized.......2006-06-11

This is a graduate level text that presents advanced material and yet is easier to understand than most high school texts and could probably be used without trouble at the undergraduate level. The writing is vibrant and lucid; it is a pleasure to read. I could come up with a few minor complaints about the presentation of this or that but these comments would be silly and not very relevant.

The book contains an absolute wealth of topics. There is an interesting combinatorial approach to groups, and the book's presentation of certain topics, such as matroids and quasigroups, is among the best I have found; many books make these structures appear painfully abstract and difficult to grasp. The book is organized so that it's fairly easy to skip around, but I actually like the order in which the topics are presented.

This text makes an excellent addition to the collection of anyone interested in combinatorics, and if someone were to buy only one book on the subject, I would recommend this book. I think this would make an excellent textbook--it was used as such in one of my graduate courses, and would probably be suitable for an undergraduate course as well.

Great book for Computer Scientist.......2005-08-06

I am M.Sc.Computer Science student and work for software company. I needed a book covering aspects in Combinatorics and this is the book.

Very helpful.......2004-01-09

Combinatorics is a bit of an oddity. Although a few principles (like pigeonholing) apply in many cases, every combinatorial problem has unique features. Attacking a new situation is almost like starting all over again, unless you can recognize an old problem in your new one.

This book gives a number brief case studies. Its 18 chapters (not counting intro and closing) span a variety of interesting topics. Cameron doesn't write down to the reader - it takes serious thought and some mathematical background to get full value from the reading. The examples are nowhere near as concrete as you'd expect in a popularized version. Still, the author avoids opaque references to specialist terms, and keeps the text approachable.

Book Description

Numerical methods that preserve properties of Hamiltonian systems, reversible systems, differential equations on manifolds and problems with highly oscillatory solutions are the subject of this book. A complete self-contained theory of symplectic and symmetric methods, which include Runge-Kutta, composition, splitting, multistep and various specially designed integrators, is presented and their construction and practical merits are discussed. The long-time behaviour of the numerical solutions is studied using a backward error analysis (modified equations) combined with KAM theory. The book is illustrated by many figures, it treats applications from physics and astronomy and contains many numerical experiments and comparisons of different approaches.

The Symmetric Group: Representations, Combinatorial Algorithms, and Symmetric Functions, Second Edition (Graduate Texts in Mathematics)

Average customer rating:

Worth the price just for the first chapter
Near Perfect
Good introduction for representation theory.
Good introduction for representation theory.

The Symmetric Group: Representations, Combinatorial Algorithms, and Symmetric Functions, Second Edition (Graduate Texts in Mathematics)
Bruce E. Sagan
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

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Accessories:

ASIN: 0387950672

Book Description

This text is an introduction to the representation theory of the symmetric group from three different points of view: via general representation theory, via combinatorial algorithms, and via symmetric functions. It is the only book to deal with all three aspects of this subject at once. The style of presentation is relaxed yet rigorous and the prerequisites have been kept to a minimum¿undergraduate courses in linear algebra and group theory will suffice.

Customer Reviews:

Worth the price just for the first chapter.......2007-02-08

Sagans book makes representation theory easy. The book first covers representations using modules and then choosing a basis to show the matrix approach. With every new topic he develops it using what Doron Zeilberger has dubbed the Gelfand Principle ([...]) The principle is: "Always chooses the smallest example to make a point". It isn't easy to find the smallest example when Sn grows as quickly as it does, but Sagen always manages to do it.

The ensuing chapters follow in the same vein. Ideas are introduced and explained, sometimes with pictures, sometimes with calculations, but always as clearly as can be.

To read this book does require a firm grounding in linear algebra, as well as abstract algebra. Time reading it is time well spent.

Near Perfect.......2003-04-06

This book is excellent. The material is presented clearly and concisely. It makes the subject matter accessible and interesting. I used it as the text for a one-semester graduate subject. I completed all of the exercises, so it is well-paced for this kind of study. I started with only an introductory knowledge of group theory, so it is self-contained. The only drawback is that there are no solutions to any of the exercises. If it had this, it would be a perfect bok.

Good introduction for representation theory........2000-03-25

This book has 4 chapters.Chapter1 is about general theory of representations of finite group.Chapter2 is about representation of symmetric groups.chapter3 and 4 are about combinatorial topics and symmetric functions. Though I haven't read all of the book,I highly recommand this book because this book shows us introductive part of representation theory with easy words.I think it is worth to read for all who are to begin the study of representation theory.

Good introduction for representation theory........2000-03-25

Parallel Scientific Computing in C++ and MPI: A Seamless Approach to Parallel Algorithms and their Implementation

Average customer rating:

101 things to do with your pet supercomputer
Should be improved.
Combining mathematics with modern computing
Great book to get acquainted with numerical analysis

Parallel Scientific Computing in C++ and MPI: A Seamless Approach to Parallel Algorithms and their Implementation
George Em Karniadakis , and Robert M. Kirby II
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Paperback

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ASIN: 0521520800

Book Description

This book provides a seamless approach to numerical algorithms, modern programming techniques and parallel computing. These concepts and tools are usually taught serially across different courses and different textbooks, thus observing the connection between them. The necessity of integrating these subjects usually comes after such courses are concluded (e.g., during a first job or a thesis project), thus forcing the student to synthesize what is perceived to be three independent subfields into one in order to produce a solution. The book includes both basic and advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Advanced topics include wavelets, high-order methods, non-symmetric systems and parallelization of sparse systems. A CD-ROM accompanies the text.

Customer Reviews:

101 things to do with your pet supercomputer.......2006-09-11

Scientific parallel computing is what this book is all about, and it does a very good job kneading MPI into the mathematical dough. The book assumes knowledge of mathematics (through Calculus, in some sections, and quite a bit of linear algebra) and little programming experience. This is not a book on C++ programming (not even close, and it does not pretend to be), nor is it a book on MPI programming, parallel computer design, or even the setting up of a suitable software development environment. In fact, it assumes all of the above, which leaves the way uncluttered for the exploration of the application of parallel algorithms upon familiar mathematical concepts.

An introductory C++ section is provided to get things rolling, though the level of C++ in the book amounts to simple classes and cin / cout in lieu of C's `printf' nonsense. This is good news, because it maintains the book's focus on the parallelization of mathematical procedures rather than on the irrelevant details of how cute it would all look wrapped up in a needlessly complex object hierarchy. Basic applied C++ and MPI, as and when needed to get the job done.

I personally use this text at home on my home-grown parallel Linux computer to investigate the partitioning of algorithms, such as going from a complex function to a Taylor series that may then be distributed to compute nodes.

Further MPI, C/C++, and extremely high-level parallel concepts are introduced through the book in a natural progression, as the problems at hand require their introduction. This keeps the book from being bogged down and off-topic. Kudos to the authors for remaining on course through a sea of such tempting distractions.
The book is the `how'. BYOW:)
ps: my CD was damaged so couldn't evaluate it.
4-stars

Should be improved........2006-02-20

The authors attempted to combine introductory material in C++, numerical methods and parallel computing. That is quite a brave endevaour. They certainly break the new ground writing an introductory material for a "simulation scientist", but I believe they have achieved mixed success.

On the one hand, the material they present on all subjects is really top quality, packed with 100% usefull information. Bibliography is also very good and usefull. But the organisation of the book is quite confusing. They introduce all the topics toogether - throughtout the book. Hence each chapter introduces some numerical algorithms, few new concepts in C++ and eventually MPI. I beleive a novice would experience serious difficulties following it. For example, authors introduce objects before introducing curly braces "{}" as scope delimiters and before semicolon ";" as statement delimiters.

Further, very soon after introducung the very basic concepts in C++, the authors move on to BLAS. BLAS is usefull, of course, but a novice in C++ may wonder why does he needs libraries written in Fortran, if C++ is a language of the choice for numerical computations. (At least it is claimed so by the authors).

Another confusing example is the one of memory memory access. In section 2.2.6 Memory Management, (pg. 41) the authors introduce basic concepts of memory management and how can loop constructs influence the efficiency of the code. Very usefull indeed, no question about it. But very soon bellow, in section 2.2.8 Exploiting the Structure of the Sparse Matrices, they come up with the claim (pg. 58): "... optimization-savy individuals, as the old saying goes, often miss the forest for the threes" :-( Hence, a novice reader might think: "Well, why do I need to worry about the memory management explained just 17 pages above?".

My most serious critic of this book by far (and I hope the authors will read this) are the contents pages. The contents list only chapters and first level sub-chapters. Secind level chapters are not present!!! That makes the book very hard to use as a reference material. That is really a pitty, since there is some good material in it which is hard to find and might stay hidden. (For example, the chapter I mentioned above: 2.2.6 Memory management is NOT in the contents, so I had to browse slowly throught the book to find it and refer it here). I suggest the authors introduce: "Contents at a glance" (the present one) and a "Detailed Contents", where one could find references to all the chapters in the book. The contents is THE reason why I gave this book 3 stars instead of 4. One it lost on the confusing organisation of the book.

I think the authors should have organised the book in four parts: 1 - Numerical algorithms, 2 - C++ and 3 - Parallel computing with MPI, 4 - Advanced topics. Part 1 could introduce numerical algorithms and have pointers to their implementations in Part 2 and corresponding parallel implementations in Part 3. Part 2 and 3 could have started with introductions, which a reader already familiar with those subjects, could skip. Part 4, could bring advanced topics, such as optimisation, BLAS, etc.

Bottom line, it is:

- brave and usefull endevaour,
- full of excellent material,
- organized confusingly,
- and has a very poor contents.

Buy it if you are simulation scientist or teacher, but prepare to struggle with its organisation and contents.

Combining mathematics with modern computing.......2005-09-30

The book contains advanced numerical mathematics algorithms and
fundamental elements of parallel computation.
It will be useful for those academic instructors who believe that students should be shown the entire solution process
from mathematical problem definition to computer implementation. It has been used as a textbook at several leading American and European universities.
The authors professors Karniadakis and Kilby are innovators who demonstrate that combining education of applied mathematics with computer science is possible and extremely useful for students and their future employers.

Great book to get acquainted with numerical analysis.......2005-06-02

This book is great in describing some of the most important concepts and algorithms needed for the beginning numerical analyst. The book claims that it can be picked up by a complete novice and teach C++, MPI, and scientfic computing. I would say that the math goes very quickly and not quite as rigorous as necessary for the typical novice. The C++ is pretty basic but still the book leaves the reader a sense of confusion. This is largely because the book treats a large amount of the library functions as black boxes. The MPI starts very basic and gradually introduces the major concepts.

My recommendation for anyone reading the book is to supplement it with a good linear algebra book (such as Demmel) and book on C++ (The C++ programming language). For further study on MPI, Using MPI would be a good supplement. That way whenever you have a concept that isn't fully described, you have a source to get it from.

The book gets a high rating for going over the right content and doing so in a applied manner that gives the reader the skills to become a numerical analyst.

Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL

Average customer rating:

Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL
Morton J. Canty
Manufacturer: CRC
ProductGroup: Book
Binding: Hardcover

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ASIN: 0849372518

Book Description

With an ever-increasing availability of aerial and satellite Earth observation data, image analysis has become an essential part of remote sensing. Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL combines theory, algorithms, and computer codes and conveys required proficiency in vector algebra and basic statistics. It covers such topics as basic Fourier transforms, wavelets, principle components, minimum noise fraction transformation, and othorectification. The text also discusses panchromatic sharpening, explores multivariate change detection, examines supervised and unsupervised land cover classification and hyperspectral analysis. With programming examples in IDL and applications that support ENVI, it offers many extensions, such as for data fusion, statistical change detection, clustering and supervised classification with neural networks, all available as downloadable source code. Focusing on pixel-oriented analysis of visual/infrared Earth observation satellite imagery, this book extends the ENVI interface in IDL in order to implement new methods and algorithms of arbitrary sophistication. All of the illustrations and applications in the text are programmed in RSI's ENVI/IDL. The software and source code is available for download at: http://www.crcpress.com/e products/downloads/default.asp. Ideal for undergraduate and graduate student, this book provides exercises and small programming projects at the end of each chapter. A solutions manual is also available.

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