Self-Organizing Maps

Book Description

The Self-Organizing Map (SOM), with its variants, is the most popular artificial neural network algorithm in the unsupervised learning category. Many fields of science have adopted the SOM as a standard analytical tool: in statistics,signal processing, control theory, financial analyses, experimental physics, chemistry and medicine. A new area is organization of very large document collections. The SOM is also one of the most realistic models of the biological brain functions.
This new edition includes a survey of over 2000 contemporary studies to cover the newest results; the case examples were provided with detailed formulae, illustrations and tables; a new chapter on software tools for SOM was written, other chapters were extended or reorganized.

Customer Reviews:

I love this book........2000-03-11

This is a wonderfully written, and excellent book. It assumes only minimal background knowledge but imparts a great deal of insight. I love the way that the author describes this area and the connections with deep and beautiful mathematics.

A very nice 'handbook' of sorts for users of SOMs........1999-08-05

The material is presented clearly and comprehensively from the unique perspective of the SOM originator himself. The inclusion of exhaustive references is particularly useful for the prospective researcher, but, at the risk of sounding ungrateful, I'm curious as to why paper titles were not included in the citations? Overall though, a very good reference.

Neural Networks: A Comprehensive Foundation (2nd Edition)

Average customer rating:

Good info, heavy on the math, but too preachy and not for the faint of heart.
A good book with a very mathematical viewpoint
Neural Networks Foundations
Very Mathematical
Need practical examples.

Neural Networks: A Comprehensive Foundation (2nd Edition)
Simon Haykin
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

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Neural Networks for Pattern Recognition
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ASIN: 0132733501

Customer Reviews:

Good info, heavy on the math, but too preachy and not for the faint of heart........2007-08-06

An excellent entry level text on the subject. The author covers most aspects of neural networks, although not quite as in depth as I had hoped in some areas. Suitable for use as a textbook if you are taking a class on the subject, or as a self study book. Gets a bit too preachy and defensive about the practicality of neural networks. The author obviously cut his teeth in NN's during the 60/70's. IMO anyone who already bought the book doesnt need convincing that neural networks work. I recommend at least a working knowledge of calculus and statistical analysis.

A good book with a very mathematical viewpoint.......2007-04-15

If you are going to start learning neural networks, this is probably the best book with which to begin. It does a good job in how it progresses through the subject. It spends two chapters introducing the subject in a very complete fashion, then five chapters more on the subject of supervised learning with neural networks, and five more chapters on unsupervised learning. The final three chapters gets off into the subject of non-linear dynamical systems.

Although the book is very complete, it is also mathematically rigorous. To really understand it from cover to cover you would need to know - both conceptually and practically - calculus, linear algebra, adaptive signal processing, and dynamical systems, since this book assumes you already know these subjects and makes heavy use of their properties. Fortunately, to get a good basic understanding of what neural networks are and what they can accomplish, you won't need to understand the entire book. I found chapters 1-7 to be fairly accessible and self-contained. It is only once you get past the subject of supervised learning in chapter eight that the mathematics and the book get particularly difficult. Another problem with the book is that it abruptly goes from a forest to a trees viewpoint of neural networks. It will be working along in a very theoretical manner for some number of pages, when suddenly, out of nowhere, it will mention something practical or show an example that clarifies a great deal. Therefore you will need to read the book carefully.

My personal recommendation is that you go through the first seven chapters of this book to get a good viewpoint of the theoretical basics of neural networks and supervised learning, and then read Jeff Heaton's "Introduction to Neural Networks with Java" to get a good practical viewpoint on the subject. Then, if you need to return to the book for the more advanced chapters, you will be better prepared. It would also be best to use this book in conjunction with taking a course on the subject. I think it would be very rough going to try to understand this book via self-study alone.

Neural Networks Foundations.......2006-08-10

This is the first book for everyone interested in the subject. A well-written and well-illutrated encyclopedia of Neural projects, including all the fundamental questions at the forefront of research in Neural Networks. I believe this is the reason for it beeing widely referenced by almost all the authors in the subject.

Very Mathematical.......2006-05-07

I used this as a textbook for a Neural Networks course I did in the second year of my undergraduate program in Mathematics and Computing.

My mathematical background till that point of time comprised Linear Algebra and upper level Calculus. This being rather 'limited' mathematical exposure, I found the book quite difficult to follow. It becomes harder when you are expected to convert the mathematical equations into working programs (without using tool-boxes or libraries, i.e.). The end-of-chapter exercises are pretty hard, and try to go beyond what the text talks about, most undergraduates may not be able be able to appreciate that. I think this is an excellent reference book for those who are pretty comfortable with Math. For undergraduates doing a first course in Neural Networks, I strongly recommend Timothy Masters' "Practical Neural Network recipes in C++". The math there is manageable, and yes, it comes with working code to make your life easier.

Need practical examples........2005-07-25

About theory, the book is good, but; it needs more practical or numerical examples, in order to get the information understandable.
There are too many concepts and ideas that without a good example, it is very hard to assimilate.
Also the computer oriented experiments in matlab, do not use the
neural network tool box, so it is not possible to get the gap to convert knowledge into computer code.
If these two recommendations are improved in a next edition, the book will become and excellent one.

thanks,

Average customer rating:

Comprehensive Book
Nice and detailed description of ICA

Independent Component Analysis
Aapo Hyvärinen , Juha Karhunen , and Erkki Oja
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover

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Independent Component Analysis: A Tutorial Introduction (Bradford Books)
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ASIN: 047140540X

Book Description

A comprehensive introduction to ICA for students and practitioners
Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more.
Independent Component Analysis is divided into four sections that cover:
* General mathematical concepts utilized in the book
* The basic ICA model and its solution
* Various extensions of the basic ICA model
* Real-world applications for ICA models
Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

Download Description

A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more. Independent Component Analysis is divided into four sections that cover: * General mathematical concepts utilized in the book * The basic ICA model and its solution * Various extensions of the basic ICA model * Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

Customer Reviews:

Comprehensive Book.......2001-10-30

Independent Component Analysis is a young and interesting topic that gained attention and still receiving more of it.

Until now this is the best introduction that has been written.
It is comprehensive, clear and unbiased.

I think that the book is a step toward making the subject not only a common field of research but also a reference for those looking for new challenging topics.

What worths mentioning is that the authors are very envolved in the development of the theory of ICA ,other books are good but are deviated by their author's own approachs and this is normal but unhealthy for a first book on any field.

What constitutes a great help for understanding ICA are the relatively easy concepts if one just intend to pick an algorithm(ex:FastICA), but this is not the case regarding its theory.

One colleague once argued that ICA should have emerged long before the begining of the 90's, claiming that Gaussian forms
(Central Limit-Theorem) killed the idea of dealing with other kinds of distributions and therefore the signal processing community went assuming every thing was gaussian (noise was gaussian,signals are gaussian),but the emerge of HOS relaxed the gaussian restriction and ICA became possible and no longer 'blind' .

I think this should prepare researchers to deal with coming challengs more intelligently and efficiently .That is why I recommend this book since it tries to give a broad view to the subject .

Nice and detailed description of ICA.......2001-10-27

This is a nice and self-contained book on the subject of independent component analysis (ICA). The authors start with relevant mathematical and statistical background (in Part I) to prepare readers for the derivations of ICA (though seasoned researchers may want to skip the first part of this book). The authors discuss the motivation behind ICA and present several ways to derive ICA (since this subject has been approached by several communities). The authors also compare and discuss the pros and cons of these approaches. The authors discuss several applications using ICA in Part III.

Book Description

"Optical communications and fiber technology are fast becoming key solutions for the increasing bandwidth demands of the 21st century. This introductory text provides practicing engineers, managers, and students with a useful guide to the latest developments and future trends of three major technologies: SONET, SDH, and ATM, and a brief introduction to legacy TDM communications systems.

There are clear explanations of:

How ATM is mapped onto SONET/SDH
The role of IP networking with ATM
Dense wavelength division multiplexing (DWDM)
The future direction of convergence of communications.

This concise book features easy-to-follow illustrations, review questions, worked examples, and valuable references. An accompanying CD-ROM provides the key figures in full color, suitable for easy cut-and-paste presentations. UNDERSTANDING SONET/SDH AND ATM is a must-read for communication professionals who want to improve their knowledge of this emerging technology."

Sponsored by:
IEEE Communications Society

Customer Reviews:

Great buy for the starters in this field.......2003-11-07

For any one trying for introduction to the topics SONET/SDH ATM This book is the best. Very lucid explanation with lot of good figures and mainly you can read it at bedtime/while travelling and get authentic overview of the subject , A must for the managers in the field and engineers starting to work in the field. The main feature is that it packs a lot of information in such a compact book and which is very well readable.

Very basic introduction and overview of SONET and ATM.......2003-04-28

This book is certainly not a in-depth/exhaustive documentation of SONET and ATM. However, it does provide a general understanding of how SONET/ATM fits in the grand scheme of things. It explains some of the obvious facts of why things are the way they are (e.g. 4Kbps BW of human voice signal, and therefore 8Ksps by Nyquist's sampling theory).
I do agree with Newport Beach reader that there seems to be some errors (I didn't know Shannon is accredited with 2X sampling theory, I have never heard of frequency hopping associated with DMT, usual just CDMA/SS).
I do find the book well organized and ideas flow in continuous manner. This is good for picking up buzz words but be prepared to look elsewhere for a full explanation. As an example, it mentions about optical components such as EDFA and pumps. If you know what these components are, then everything flows. If not, then you'll have to google.
Book should be good for manager/sales people. Even an average engineer with minimal experience (like me) would find it too brief. This is the kind of book for bedtime reading (i.e. no equations) and would most likely sit on the shelf after.

Lots of errors and not a good explanation of SONET.......2001-01-23

This book was published by the IEEE. It lists two technical reviewers (Curtis Newton and Kevin Sparks) and the author thanks certain anonymous reviewers, I assume, in addition to Newton and Sparks. And yet, the book has an amazing number of errors, even to my quick reading. For example, on page 4 he credits Shannon as developing the criteria that you must sample at twice the bandwidth of interest, when this is generally credited to Nyquist (even Shannon credits Nyquist). On page 10, he claims that 2B1Q is limited to 392 Kbps, when 2B1Q is used on HDSL to provision T1 lines at 1.544 Mbps over two pair (about 784 Kbps over each pair). Extensions to the standard by companies such as Conexant have pushed 2B1Q to about 2.046 Mbps on a single pair. Also on page 10, he associates "frequency hopping" with DMT, instead of wireless spread spectrum. He also claims that CAP modulation can only achieve data rates of 10-175 Kbps. I'm sure the engineers at Globespan will get a chuckle out of that. On page 66, there's an error in Figure 8.9. On pages 55, 56, and 57, his explanation of pointer adjustments has an error on when the pointer is adjusted. And that's just with a quick review (maybe 30 minutes).

But perhaps more importantly, his explanation of SONET/SDH is just not very thorough or clear.

Unfortunately, I can't point you at a good book on SONET/SDH. All of the books I looked at just don't do a good job of explaining it. If you already know the technology you can read the books and understand them, but if you're just starting out you'll get lost in a hurry.

For a good explanation of the network, in general, the best book I've found is Bellamy's "Digital Telephony," 3rd edition. His explanation of SONET, while accurate, is too brief for a novice, however.

Take SDH out of the title........2000-12-31

With the current explosion of SDH networking across the globe, a reader would expect a little more substance on SDH in a book that claims to also cover SDH. While the book does highlight SDH in a few chapters, it lacks greatly and cross-references much information on SDH to SONET. While SONET and SDH are similar, they are not the same and the book can confuse readers wanting to learn about SDH by referencing SONET rates in an SDH chapter. I wish some of these authors would get off the SDH bandwagon and stop trying to write something in an area that appears to be outside their expertise. This book is a book about SONET and ATM. For any reader wishing to learn more on SDH, this book is NOT the book to read. The only thing I found useful in this book was the figures available on the CD inside the cover. What I do with the book now is let it collect dust on my bookshelf.

Ample illustration / Inordinary approach.......2000-11-12

The book is thin ( less than 300 pages ). However, it covers 2 topics: SONET and ATM. It goes in a slightly abnormal way to arrange the content: Many detail facts, less explaination. For example, it provides a huge amount of figures in comparison with other books. There are some sentances describing the coverage of SONET on OSI-RM to be from layer 1 to layer 7, but no further discussion to tell us why? It does give us a crue to refer to the GR documents of Bellcore, but this apears to be another difficault problem. It's also a pity of lacking completeness. For example, TMN is not mentioned here; while in other books TMN occupies a certain space for its expectation to operate SONET management. All the cases above apple to the 2nd half of this book, ATM.

Book Description

New technologies in engineering, physics and biomedicine are demanding increasingly complex methods of digital signal processing. By presenting the latest research work the authors demonstrate how real-time recurrent neural networks (RNNs) can be implemented to expand the range of traditional signal processing techniques and to help combat the problem of prediction. Within this text neural networks are considered as massively interconnected nonlinear adaptive filters.

Ø Analyses the relationships between RNNs and various nonlinear models and filters, and introduces spatio-temporal architectures together with the concepts of modularity and nesting

Ø Examines stability and relaxation within RNNs

Ø Presents on-line learning algorithms for nonlinear adaptive filters and introduces new paradigms which exploit the concepts of a priori and a posteriori errors, data-reusing adaptation, and normalisation

Ø Studies convergence and stability of on-line learning algorithms based upon optimisation techniques such as contraction mapping and fixed point iteration

Ø Describes strategies for the exploitation of inherent relationships between parameters in RNNs

Ø Discusses practical issues such as predictability and nonlinearity detecting and includes several practical applications in areas such as air pollutant modelling and prediction, attractor discovery and chaos, ECG signal processing, and speech processing

Recurrent Neural Networks for Prediction offers a new insight into the learning algorithms, architectures and stability of recurrent neural networks and, consequently, will have instant appeal. It provides an extensive background for researchers, academics and postgraduates enabling them to apply such networks in new applications.

VISIT OUR COMMUNICATIONS TECHNOLOGY WEBSITE!
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VISIT OUR WEB PAGE!
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Customer Reviews:

I should buy it in 2001........2007-09-19

I give this book 5 stars. It is a must have book, very well written. It has good balance between rigorous theory and authors reasonong regarding the subject.
I'm not a beginner in this field, and still I found a lot of interesting ideas, that can help not only to improve quality of the net, but also make you see "bigger picture".

Unexpected insights that make you go: "Aha!".......2001-11-28

"Recurrent Neural Networks for Prediction: Learning Algorithms,
Architectures and Stability," approaches the field of recurrent neural networks from both a practical and a theoretical perspective. Starting from the fundamentals, where unexpected insights are offered even at the level of the dynamical richness of simple neurons, the authors describe many existing algorithms and gradually introduce novel ones. The latter are convicingly shown to yield better prediction performances than traditional approaches, when applied to real-world data. They also dedicate a considerable amount of time on the (practical) issue of nonlinearity analysis of time series, which is or should be, indeed, the cradle of all proper modelling and/or filtering solutions: nonlinearity should be assessed prior to choosing the appropriate model and/or filters, since linear ones are to be preferred if sufficient for the problem. I would recommend this book to any researcher who is active in the field of recurrent neural networks and time series analysis, but also to researchers who are new in the field, since the book offers an extensive overview of the current state-of-the-art approaches.

Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics

Average customer rating:

The only book on this important subject in print

Vector Space Projections: A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics
Henry Stark , and Yongyi Yang
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover

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Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)

ASIN: 0471241407

Book Description

A guide to the theory and application of methods of projections.

With the rise of powerful personal computers, methods of vector space projections have moved rapidly from the realm of theory into widespread use. This book reflects the growing interest in the application of these methods to problem solving in science and engineering. It brings together material previously scattered in disparate papers, book chapters, and articles, and offers a systematic treatment of vector space projections.

Written by two leading authorities in the field, this self-contained volume provides a tutorial on projection methods and how to apply them in science and engineering. It details effective problem-solving strategies, and explores key applications in communication and signal processing, neural networks and pattern recognition, and optics and image processing. This book:

Reviews the fundamentals of vector space theory
Covers principles and applications of vector space projections in general, and projections onto convex sets in particular
Provides real-world examples solvable on PCs and modest workstations
Features more than 100 illustrations
Includes end-of-chapter exercises and references.

This extremely useful reference for practicing engineers, scientists, and educators can also be used for graduate-level study in science, mathematics, and engineering. Portions of the book have been used as material in short courses on applications of vector space projections.

Customer Reviews:

The only book on this important subject in print.......1999-11-18

This book showed me how vector space methods are a natural way to use the computer for solving difficult problems in engineering design. Although my background in mathematics consists only of advanced calculus and linear algebra, I had no trouble following the theory and learning the applications. For electrical engineers, such as myself, the applications to digital filter design were particularly interesting. There are many other applications described, including the design of lenses, image processing, even neural nets. What I like is that the authors give the backgroud to each application so that even if you are unfamiliar with the field, there are clear and concise introductions that help your understanding of the problem. For example, in the digital filter design section, the authors explain why digital filters are important and how they relate to analog filters. To write a book like this takes not only broad knowledge but extraordinary expository skills.

Computer Networks: A Systems Approach (Morgan Kaufmann Series in Networking)

Average customer rating:

A good primer to computer networks and its design
Good for Academic Studies. But...
A good general introduction, not an engineering textbook.
Excellent book
Too Confusing

Computer Networks: A Systems Approach (Morgan Kaufmann Series in Networking)
Larry L. Peterson , and Bruce S. Davie
Manufacturer: Morgan Kaufmann Publishers
ProductGroup: Book
Binding: Hardcover

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Operating System Concepts

ASIN: 1558605142

Amazon.com

Computer Networks: A Systems Approach, designed for an advanced college-level course in network design and operation, provides the network applications programmer with detailed information about how networks do their thing. While Computer Networks is neither a user manual nor a technical reference, it provides an in-depth background on how network architectures and protocols work.

In the beginning, Larry Peterson and Bruce Davie discuss why networks are important and talk about where networks may go in the long term. The authors then move right into a discussion of protocols. There's a fascinating section--complete with plenty of C code--in which the authors actually develop a network protocol called A Simple Protocol (ASP). They compare switching and packet networks and emphasize tunneling protocols. In the internetworking chapter, you'll learn practically all there is to know about Internet Protocol (IP). The concluding chapters talk about traffic management, congestion reduction, and high-speed networking technologies.

Computer Networks reveals the guts of what's going on with computers that share data. Though way out of the league of most computer users, true geeks with an interest in networking will find what they need here.

Book Description

Networking technologies and practices are constantly evolving. Equip your students with an understanding that helps them keep pace with Internet time.

In this carefully focused revision of the best-selling first edition, authors Peterson and Davie reiterate their commitment to a systems-oriented approach to networking instruction. Focusing on the why of network designÃ¢Â€Â”not just the specifications comprising today's systems but how key technologies and protocols actually work in the real world to solve specific problemsÃ¢Â€Â”they promote an enduring, practical understanding of networks and their building blocks.

The second edition incorporates coverage of Quality of Service issues, mobile and wireless networks, VPNs, and much more. Over 100 new exercises help users consolidate and expand their knowledge.

No other textbook offers a more solid grounding for aspiring network professionals. Computer Networks: A Systems Approach gives your students the knowledge and perspective they need and gives you the tools you need to maximize their learning experience:

* Unparalleled instruction from an expert team of authors. The authors bring over 30 years of experience in networking research, development and teaching to the task of describing the principles and practical implementation of computer networks. Both have played key roles in defining and implementing many of the protocols discussed inside.
* Cutting-edge coverage. The second edition has been thoroughly updated to cover the most recent advances in networking, including:

* a new chapter on security techniques - PGP, IPSEC, secure sockets and firewalls
* a new chapter on application layer protocols Ã¢Â€Â“ SMTP, HTTP, SNMP, DNS and RTP
* new material on wireless and mobile technology- spread spectrum techniques and 802.11
* new section on building VPNÃ¢Â€Â™s on top of the public Internet

* Expanded treatment of key issues. Topics such as Internet routing, Quality of Service, congestion control, ATM, compression and multimedia communications now delve deeper to reflect changes that have taken place over the past four years.
* Effective pedagogical components. Alongside the authorsÃ¢Â€Â™ clear explanations and insights, youÃ¢Â€Â™ll find pedagogical components that significantly enhance studentsÃ¢Â€Â™ understanding:
* Problem statementsÃ¢Â€Â”the practical design challenges met by the techniques covered in each chapter
* Shaded sidebarsÃ¢Â€Â” explorations of advanced topics
* Highlighted summary paragraphsÃ¢Â€Â” distillations of key network design principles
* Open IssuesÃ¢Â€Â”guided discussions of controversial networking issues
* Further readingÃ¢Â€Â”pointers to definitive papers related to each chapterÃ¢Â€Â™s coverage
* Completely revamped end-of-chapter exercises The second edition offers over 100 new end-of-chapter exercises, the result of a substantial editing and development effort by a seasoned networking instructor, Peter Dordal of Loyola University.
* The optimal pedagogical approach. Encyclopedic and "layered" approaches cover required material but leave critical questions unanswered. Peterson and Davie focus on systemsÃ¢Â€Â”how they interweave technology and technique to meet practical needs. Adding layer-focused considerations where necessary, the authors teach students why networks are designed as they are and cultivate the skills needed to build the networks of the future.
* Real-world implementation examples. New to this edition, operating system-independent C code is used with pseudocode to illustrate protocol implementation throughout. The first editionÃ¢Â€Â™s x-kernel examples continue to be available online.

Customer Reviews:

A good primer to computer networks and its design.......2006-09-25

A comprehensive textbook for undergraduate/graduate students. The book is complete with basic coverage to different types of networks and their working. Treatment to TCP and other Internet protocols well explained with pseudo code for different algorithms. Various extensions to TCP and network security basics well covered. The book does lack some mathematical treatment to the subject which could have improved the content.

Good for Academic Studies. But..........2005-11-24

I am studying this as part of my course. I have found this book teaches you from the base about Networking. It's really helpful in understanding the underlying technologies. Larry and Bruce have done a wonderful job in covering almost all of the aspects. But... I found only one thing lacking. That is...graphical explanations. This book is more of text with required graphics but in some places it took time to visualize the concept. I have had Behrouz A. Forozan's (I hope I have spelt the name correctly) "TCP/IP: The Complete Protocol Suite" along with this. Particularly I found some of the parts like ATM, Routing and other chapters' in this book textually gives us a thorough understanding and Forozan's book does depict that visually in a better way. Here is the bottomline, have this book as "The" texbook and have some other books like the as I mentioned before.

A good general introduction, not an engineering textbook........2005-01-27

Although this book clarifies the concepts of networking quite good, it lacks in-depth mathematical & statistical theory.
For those who are interested in the general picture, it's an excellent book. The authors actually succeeded quite good in not making it 'too dry'. For those who need 'more', like engineers and students in telecommunications/electronics, such as theories, applications and examples on efficiency, network performance parameters, etc., please look further as this book just doesn't offer that (and it probably never intended to).

Excellent book.......2004-10-14

I've been dealing with computer networks in theory and practice for quite some time. This book is excellent reference and give in depth details and knowledge. The structure is well designed and the materials are following each other. If you are looking for a startup book though, this might not be the right choice.

Too Confusing.......2004-07-29

This book is designed for someone who has prior knowledge with the underlying systems of a computer network. It is fairly in-depth, and explains a lot, but I think that for a true beginner it is hard to comprehend. I am working on a degree in Computer Science, so it wasn't like I was new to the idea of networking, but I found it hard to digest a lot of the technical aspects of this book. Some things could have been made to be more of an overview, rather than in-depth explanation of how something works at a bit level. I am now taking CCNA training, and some of the things talked about in this book do not relate at all to what someone needs to understand a working network.

Fuzzy and Neural Approaches in Engineering, MATLAB Supplement (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)

Average customer rating:

starter

Fuzzy and Neural Approaches in Engineering, MATLAB Supplement (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
Lefteri H. Tsoukalas , Robert E. Uhrig , and Lotfi A. Zadeh
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Paperback

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Similar Items:

Fuzzy and Neural Approaches in Engineering (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence
Introduction to Fuzzy Logic using MATLAB

ASIN: 0471192473

Book Description

Neural networks and fuzzy systems represent two distinct technologies that deal with uncertainty. This definitive book presents the fundamentals of both technologies, and demonstrates how to combine the unique capabilities of these two technologies for the greatest advantage. Steering clear of unnecessary mathematics, the book highlights a wide range of dynamic possibilities and offers numerous examples to illuminate key concepts. It also explores the value of relating genetic algorithms and expert systems to fuzzy and neural technologies.

Customer Reviews:

starter.......2000-10-15

It seems that most texts on fuzzy and nnets are in very basic form. Given the (fact) substantial use of both types of controllers at the most advanced levels of technology and finance it seems somewhat strange (trade secrets). If you already have Matlab's Fuzzy or NNets the material is somewhat redundant, given that the M-files are easier to work with in Matlab than using the Microsoft Word connection (more later). The manual allows the basic concepts to be easily transported to MathCad and for this reader is worth the book. It is for the begginer without Matlab that this text really shines. It has the Microsoft Words ability to work with the Matlab (although it is not installed) interface to show the reader how the two,fuzzy and nnets, work together. At the very least it allows someone to determine if they wish to proceed with topic (this is the future of control systems). I found that building a sub program in MathCad using set theory operators, to call the sub-routines of fuzzy and nnets worked best. This was a just for fun. Both Matlabs Fuzzy and nnet toolboxes work far better. This text adds fill in material for both Matlabs fuzzy and nnet toolbox texts.

Intelligent Methods in Signal Processing and Communications

Average customer rating:

Intelligent Methods in Signal Processing and Communications

Manufacturer: Birkhäuser Boston
ProductGroup: Book
Binding: Hardcover

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ASIN: 0817639608

Average customer rating:

It's exactly what the title states, "Adaptive Filter THEORY"
Not a bad reference book.
A very good book for Adaptive DSP...
Adventures in the development of stochastic DSP
Adventures in the development of stochastic DSP

Adaptive Filter Theory (3rd Edition)
Simon Haykin
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

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Similar Items:

Adaptive Signal Processing
Fundamentals of Adaptive Filtering
Fundamentals of Statistical Signal Processing, Volume 2: Detection Theory
Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory
Statistical Digital Signal Processing and Modeling

ASIN: 013322760X

Customer Reviews:

It's exactly what the title states, "Adaptive Filter THEORY".......2005-03-17

I was introduced to this text in a graduate course. I was not too thrilled about learning from another Haykin book due to a previous experience with his Communication Systems text in an undergraduate course (Horribly confusing... Proakis's text is infinitely better). To my surprise, the book was very detailed and easy to read. The math is very clear and detailed (great for the self learner). Also, the second chapter, which serves as a review of stationary processes and properties, was written much better than most random process textbooks (I applaud Haykin for this given the section was only a review). In chapter 3 or 4, he shows the derivation of the Levison-Durbin Algorithm step-by-step. I strongly disagree with some of the other reviews stating this text is just the typical engineering manual or cookbook with no explainations.

However, this is either a love or hate text. If you are looking for a text about practical linear predictive filter design, this is NOT the book for you. This text is heavily geared towards understanding the theory behind the design... hence the title Adaptive Filter THEORY. However, it can make a great reference to engineers in the field of DSP.

Not a bad reference book........2004-06-17

This book looks very impressive, but if you try to understand it you'll find it very mechanical. There is not much motivation behind the many pages of formulas and derivations. I'm not even sure how many people actually read those derivations becuase even in its 4th edition the book and its solution manual both have many typos (see, for example, equations 8.11 and 12.5). Even the problems are more focused on derivations than on numerical examples. This is a good cookbook if you just want to implement an algorithm or find some pointers to the original research papers. Like many other reviewers, I beleive that engineering textbooks are losing their depth and becoming more and more like instruction manuals.

A very good book for Adaptive DSP..........2001-05-09

I have always wondered why many people have negative opinions about books by Simon Haykin, whether it is 'Communication Systems' or 'Adaptive Filter Theory'. Particularly, this book 'Adaptive Filter Theory', in my opinion, is one of the bestbooks on this subject. As Julius Kusuma correctly mentioned, this book is indeed an "adventure ride" into the field of Adaptive Filter Theory.

I discovered this book when I was doing a class project on Self-Orthogonalizing algorithms for Adaptive Beamforming and I felt that all the relevant information that I needed was present in this book. I did'nt really feel the neccesity to refer anything outside this book.

Apart from that, this book contains everything that a graduate student needs to know about this exciting field of adaptive filters. The author assumes some background on Random Signal Theory... I'd suggest to look up Sam Shanmugan et al's, "Random Signals: Detection, Estimation and Data Analysis" before beginning to read (enjoy) this "adventure ride" on Adaptive Filters.

Adventures in the development of stochastic DSP.......2000-07-24

Despite the commonly negative opinion against Simon Haykin's book, I find this book to be a very fun reading. It starts off with a very brief review of DSP (more useful just for getting familiar with the notation, really), properties of random processes, and a small section on linear algebra in the middle of the book.

The rest of the book can be viewed as a story of how different approaches and algorithms were developed, and is a little difficult to use as reference due to its lack of structure and over-dependency on the previous chapters, both for technical content and notation. I have to admit that the notation used in this book is very, very poor and can be a source of frustration. The dependency is also a pain because you always have to keep flipping 100 pages back because Mr. Haykin prefers to say "Eqn. (4.24)" instead of "an AR model".

But there's a lot of hidden treasures within this book that should have been more emphasized. For example, Mold's theorem that states that any discrete stationary process can be decomposed into a deterministic component and a random component, which are uncorrelated to each other. I'm sorry, but a reference to a proof in another book is not enough to really motivate me. This is a very fundamental theorem if you're interested in stochastic signal processing. Sure, you don't cover the Fundamental Theorem of Calculus in your very first calculus class, but then again this is supposed to be a fairly advanced book.

So if you're interested in learning certain things quickly, this is NOT the book to get. Consider Munson Hayes' book instead. Save this one when you feel like investing a little time to hear Haykin's story on stochastic signal processing.

Adventures in the development of stochastic DSP.......2000-07-24

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