Fuzzy-Logic Books

I bought this book on a whim simply because I liked the cover, and it turned out to be really funny. I enjoyed the wry humor it had to offer, some of the gags are way out in left field.

I read, I laughed! I loved it! This is a book of intelligent humor. I kept saying to myself, "Yes, I've been there..." but it wasn't funny until Eric Polster put pen to paper...

Keep a copy around the house when friends drop by....they'll love it. Eric Polster takes a slice of life, puts his own unique spin on it and the result is hilarious!" **** Four stars. Bill Diehl, ABC Radio News Entertainment Correspondent

Just when I thought there was nothing left to make me laugh here comes this talented, insightful, intelligent and very funny man, Eric Polster. The more I think about his little comic dynasty entitled - Fuzzy Logic - the funnier they get. E.P. has a way of making jokes like squeezable fruit; there's always one more drop of humor left. Hurry up with Fuzzy Logic II.

This Polster guy is great! Hard not to make comparisons with Gary Larson. His humor takes a little getting used to, but then you realize how deep and twisted it is. I love it!

An excellent option if you are looking for business and industry examples and applications of Fuzzy Logic.

If you are looking for more in-depth knowledge and theory about Fuzzy Logic you should consider "The Fuzzy Systems Handbook: A Practitioner's Guide to Building, Using, & Maintaining Fuzzy Systems" by the same author.

In this book the concepts of Fuzzy Logic are outlined reasonably well, but emphasis is put on the so called 'applicability' of fuzzy reasoning in business applications. By working through several business examples in depth, a fair coverage of the topic is provided. The step by step description of the fuzzy process is a bonus towards understanding how the model arrives at it's end results.

However, compared with the Fuzzy Logic Handbook, this book relies too heavily on the examples. It lacks the clear description of some of the underlying mathematics and their relevance provided in the Handbook aswell as a solid foundation of the principles of fuzzy logic.

On the other hand, this book provides long and detailed examples that can be usefull in combination with the sometimes short descriptions provided in the Handbook.

If you are looking for a good introduction into Fuzzy Logic, this is not the right book, if however you are somewhat familiar with the principles and want to see for yourself how fuzzy logic works, this book provides some nicely worked out examples.

This book compliments The Fuzzy Systems Handbook very well. (BTW, The Fuzzy Systems Handbook, also by Earl Cox, is one of the most usable Fuzzy Logic books that I have on my bookshelf) The practical examples in Fuzzy Logic for Business and Industry, provide users with tools to implement Fuzzy Logic in real world applications. If you want a book explaining Fuzzy Logic principles, this is not the book for you. If you want to get insight into the application of Fuzzy Logic in business scenarios, this is a very worthwhile starting point.

This exceptional book provides a broad overview of the methods of extracting the knowledge (or in other words building model/system/theory) from the data in various areas: from information theory and artificial intelligence to genetics. It can be very useful for biologists, who wish to use modern computational methods for analysis of microarray data, regulatory networks, cancer, analysis of clinical trials, etc.

The first part (first seven chapters) of the book is devoted to the methods used in connectionists systems and here readers can find detailed description of the algorithms. In the second part (six chapters), which represents application of these methods, the book has a chapter devoted to the data analysis, modeling, and knowledge discovery in bioinformatics so it can be interesting for the biologists. This chapter describes how the neural network paradigm can be used in molecular biology and, in particular, for analysis in relatively new area -- microarray technology. The huge amount of data that were obtained in this area is still waiting for the efficient methods of knowledge extracting. In this chapter readers can also find the examples of using evolving connectionists learning systems for solving the problems of finding the patterns from DNA/RNA sequences, identification of intron/exon binding sites, gene profiling, protein structure prediction and dynamic cell modeling.

This excellent book is full of interesting examples, classification schemes, and figures.
Although this book will be more interesting for readers, which have been working in networking, it can be useful also for all researchers and students and any type of readers interesting in data analysis. This book is outstanding introduction for readers unfamiliar with the learning systems. The extended glossary and full-length reference list will help a lot for readers inexperienced in this area.

I found this book to be a landmark contribution to the state-of-the-art in neural networks pardigm. It offers some exciting neural network topologies and a distinctly new kind of thinking -'local learning' in neural networks. The author Prof. Nik Kasabov deserves to be congratulated for writing this excellent book. His explanation throughout the book is very lucid and to the point. He introduces the concept of "evolving connectionism" in a succinct way. He included a rich assortment of connectionist methods, right from the scratch, with a clear exposition of the underlying training algorithms. The applications presented in the latter part of the book are as diverse as bioinformatics, financial engineering, speech recognition, brain study and image & video data processing. The authority with which these topics are presented speaks volumes of the enormous research work undertaken by Prof. Kasabov and his students. The references and extended glosary provided at the end are extremely useful to the reader. Another important aspect of this book is that it is suitable for all levels of readers such as student, researcher and practitioner. I started teaching some aspects of this book from this semester onwards. It is well received by the students. It must be in the shelves of those who look for the latest research in the area of neural networks. I enjoyed reading this book. Finally, if the phrase "real-time neural networks" is also added in the tag line (sub title) of the book, it could attract more users.

An excellent reference on Fuzzy Logic and Neural Networks.

This books covers fundamentals topics like:
- Principles and Algorithms.
- Applications.
- Architectures and Systems.

An excellent textbook edited by IEEE and with contributions from many experts on these fields.

Gain access to fuzzy logic algorithms, design guidelines, and current applications examples from signal processing and power systems to home appliance design and manufacturing with this key handbook! Featuring contributions from top names in the field, this handbook offers an in-depth understanding of the major research and activities in fuzzy logic and neural networks.

I have read about half the book so far, and like it more or less. It takes a *long* time to get a good definition of Fuzzy Logic, its components, and its process. It lacks a good section on just diagramming the process flow, however the components have a decent amount of detail dedicated to them. Some of the diagrams are self explanatory, but too much detail in text for them.

This is one of my Fuzzy Logic book's. The C++ OOP code inside will make your life simple. Easy deign can be done by simply adapt the C++ code. Usefull information and review was made by the author on the topic of Fuzzy Logic with microcontroller system !! Well if you need a practical book on Fuzzy Logic .... this is the one !!

The style of this book is excellent in that it gives you plenty of examples of how fuzzy arithmetic works. Honestly, I doubt there exists a more comprehensive book on fuzzy arithmetic around.
You'll find information on fuzzy numbers and their basic arithmetic, how alpha cuts work in fuzzy arithemtic, type-two fuzzy numbers, probabilisitic-fuzzy hybrid numbers, fuzzy modular arithmetic, combinatorics with fuzzy numbers, and an application of fuzzy arithmetic to catastrophe theory. And more, of course.
If you can find a copy, get it immediately. The explanations are clear, the reasoning is thorough, and the examples carefully illustrate the ideas. Steal this book!

I've had this book for years, and keep coming back to it. Many books define fuzzy numbers in various ways, and hint at combining them with some kind of arithmetic. Kaufmann and Gupta actually carry out those operations. Since fuzzy addition is a kind of convolution, they also show why fuzzy subtraction does not reverse the operation - deconvolution does. If you want to use fuzzy arithmetic for constraint propagation, this changes the basic nature of backwards propagation.

I just wish the author's clarity had extended a little farther into the mechanics of the various kinds of convolution. They handle discrete cases only, and offer about the least readable presentation of convolution that I've ever seen.

I'm not a theoretician, so I appreciate the book's clarity and examples. It is so clear and thorough that I refer to it for ideas quite unrelated to fuzzy arithmetic. If a sign of a great book is the number of unrelated topics that it clarifies, then this title is very good indeed.

This title may not suit the beginner and may not suit the expert. For us in the middle, though, it is incredibly helpful.

This book is an above average history of the conceptualization ,development,and application of fuzzy logic.Fuzzy logic essentially replaces the point estimates of the mathematical laws of probability(addition and multiplication rules for disjunction and conjunction,respectively)with interval estimates using linear programming techniques.The two main protaganists are L. Zadeh and B. Kosko.They certainly should be recognized for independently developing their own particular versions and approaches to interval estimates but they are NOT the originators.The authors of the book overlok that it was George Boole who was the first to come up with interval estimates for probabilities,including non rational numbers, in chapters 16-21 of his 1854 The Laws of Thought.J M Keynes then used modified versions of a number of these problems of Boole's to present a method of approximation using an interval estimate approach in his A Treatise on Probability in chapters 15 and 17.Keynes rejected the purely mathematical laws of probability as a special case and emphasized the notion of " non numerical " probabilities or indeterminate or non comparable probabilities,by which he meant interval estimates.Theodore Hailperin,in 1965 and in full length books in 1976,1986,and 1996,demonstrated that all of the Boole problems could be solved as linear programming problems.Daniel Ellsberg's "ambiguous" probabilities(intervals)are also overlooked in this book.


The authors mix subjectivist Bayesians(Ramsey,De Finetti,and Savage)with Objectivist Bayesians(Jeffreys,Jaynes)without apparently realizing that there are major differences between them.The claim that Boole reduced thinking to "classical logic " and "well bounded symbols " while ignoring " vagueness " on p.71 is false as is the claim that Boole was a supporter of the purely mathematical application of the laws of probability who rejected subjectivism at the top of p.180.He was not.

This is a entertaining book.It is worth buying even though the authors have overlooked the actual originators of the interval estimate approach to decision making based on indeterminate probabilities-George Boole,J M Keynes,Theodore Hailperin,and Daniel Ellsberg.

The book claims to be a introduction to fuzzy logic. Though I now know something about the development of fuzzy logic, it has not developed my understanding of fuzzy logic. This introduction is just too simplistic. It lets you think you understand, but you really do not. The book do not contain any logic at all, no proofs, no methods and no exercises. It should not be taken as a book on logic, but a book ofn the history of logic.

'Fuzzy Logic: A Revolutionary Computer Technology that is changing our world', a book by Daniel McNeill and Paul Freiberger, is all about the history and philosophy of fuzzy logic. This book was written nearly a decade from now and the main body consists of 275 pages of text (pp. 9 to 283). It took me 2 weeks to finish reading this book since I underlined important terms, concepts, and names of the people who contributed to the development of fuzzy logic. Without underlining, I think anyone can read this book in less than a week. The book has the following advantages and disadvantages:
Advantages:
1. It has quotations from famous people at the beginning of each chapter.
2. It is comprehensive.
3. It has been a major source of reference of most websites on fuzzy logic.
4. It is lightweight and measures approximately 7' x 5' inches.
Disadvantages:
1. It contains only a few diagrams.
2. It is monochromatic (lacks color).
3. It is generally non-technical.
I understand its predominantly non-technical approach (3rd disadvantage) because I assumed that there has been a lack of English technical references for fuzzy logic in the early 90's. Therefore, these are my comments/suggestions:
Comments/Suggestions:
1. I suggest that the authors revise the book to include 2 parts:
a. Fuzzy Logic: History and Philosophy
b. Fuzzy Logic: Concepts and Applications
2. The revised version should include more mathematical diagrams/models, sample problems with solutions, and exercises with odd-numbered solutions.
3. The revised version should include technical references such as 'Heaven in a Chip: Fuzzy Visions of Society and Science in the Digital Age' by Bart Kosko, 'Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models' by Vojislav Kecman, 'Genetic Fuzzy Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Bases' by Oscar Cordon, 'Fuzzy Engineering' by Bart Kosko, and Fuzzy Logic and Neuro Fuzzy Applications Explained' by Constantin Von Altrock.
4. The revised version should include sample applications with simulation using free downloadable fuzzy logic software/program from the internet such as FuzzyLib 2.0 and Simple Inference Engine 1.0 which are currently both available...

"Imagine a technology so revolutionary that it gives computers the ability to make decisions more like human beings"

This is a book about the history of this technology, but be aware this is not an academic, scientific or engineering book.

An excellent reading if you like to know a little bit about the behind the scenes, the lives, and stories that surround the development of this fascinating technology. Fuzzy logic is a technology so great, that in my opinion, it single handed advanced the science of artificial intelligence, in a way that it wouldn't have been possible without the concepts that support Fuzzy Logic.

As Earl Cox Said: "If you are curious about fuzzy logic, buy this book. If you are working with fuzzy logic, buy this book. If you have never heard about fuzzy logic, buy this book....The Rosetta Stone of fuzzy logic".

Again,...be aware....this is not an academic, scientific or engineering book about mathematics or logics. Its just a Hot science book about the history of Fuzzy Logic.

McNeill does a great job in picturing the initial introduction of Fuzzy Sets, rejection by US companies, and the developments of Japanese companies. This book contains the best historical recolection on Fuzzy Logic.

I finish my degree in Economics last year. For my thesis I studied and used neural networks and fuzzy neural networks. I used the text book by Kasabov and find it easy to understand, clear and full of examples, data sets and usable software. The book is excellent text for people without prior knowledge in the area. I am still using the book.

If you read this book, you won't get example C code snippits like other books have. However you will get an excellent understanding of neural networks and fuzzy systems. This book is very well written, and has lots of information! With the information in this book you could write your own code snippits and really understand how it works, rather than just using the code! I highly reccommend this book if you interested in artificial intelligence. It isn't "dry" like some books, and has examples of uses, as well as how well they work!

I am finishing my degree in environmental engineering at the Politecnico of Milan, Italy. I used this book during a project about adaptive control using neural networks applied to wastewater treatment plant's operation unit. I find it very useful; it is clear and it is possible to find together with the theory practical applications and datasets. In an easy way it shows a mental scheme of artificial intelligence foundations.

This book covers the fundamental concepts and methodologies of neural and fuzzy systems providing many significant applications in decision support, data analysis and data mining. It is a good research guide and an excellent teaching material and offers a wide outlook for future research and application directions.

I don't understand the gap between the two group of reviews ( 5 stars and 1 star). As other reviewer said, this book is just a list of techniques without proper examples and without proper math. I understood a couple because I already knew about them. If I would try to use any of the techniques I couldn't. There is more to an algorithm than half a page of description. Where are the examples, the ups and downs, the math justification ?

"Your memory is just one small database that you can access at the speed of light. You can command armies of intelligent agents and search thousands or millions of database and knowledge networks. And you can sense all store knowledge of art and science and news and history much as you scan a newspaper."

>>Frankly, there is not enough information. There will always be more search engines than information. Information will be repackaged and refractored in numerous variations, but the core information is infinite. The brains poor memory is offset by its ability to create. Can a chip create new thought? To touch the divine is to create. Creation of thought is not random. Genetic Algorithms work because all the states of the problem are known. GA converge faster when intelligent analysis reduces the number of states and more clear defines the rules.

"You can dampen or amplify pain and pleasure signals and weave new patterns of emotion or feeling and shut them off when you are tire of them."

>>Emotion is necessary element to thinking and reasoning and by shutting down the wrong emotion the individual will become disoriented and confused. Emotion is necessary for recognition and consciousness. Lose of emotion will resulting in neurological paralysis in the cognitive processes of the mind.

>>Evolution destroys morality and it cancels out a life purpose, and traps the person into believing free will does not exist. By shutting down the emotion of guilt a person shuts down the emotion that help will they avoid wrong morals behavior and chose right moral behavior. For example, it is immortal to steal and kill. Strong emotional barriers based on morality help individuals deter from acting out these behaviors. The ability to turn emotion on or off is not preferred. The power to cancel out emotion morality is the evolutionist dream; it is the perfect way to destroy any feeling of morality. The resulting behavior is destructive. A hedonist will amplify pleasurable emotions and dampen painful emotions; this will distort the perfect balance that exists in the mind.

"You can relive any past memory or modify memory as vividly as you lie the current moment. And all and some of this you can share with others in the chipnet or chiploaf."

>>If memory can be modified then it also can be reprogrammed and cloned. Memory distinction is a valuable part of existence. Memory and experience provides a distinct signature of who we are.

"In a chip time passes a million or billion times more slowly if you want to...A good crystal chip could last for thousands or millions of years or until it fell into a star or black hole."

>>A brain in a chip requires a society is a society of disembodied agents in a complex network of information interconnected with hierarchical rules of order. Complexity does not provide meaning. Increased complexity provides no advantage in terms of gain or increase for man. The loss of identity and the appreciation for individuality will be the values destroyed by assimilation. A parent and child enjoy a social communication, bond, and relationship and bring emotional satisfaction. The emotion of joy and love are prized emotions that intelligent beings desire. The acquisition of knowledge does not perpetual increase. Intelligence perpetuates increase in context and meaning. The ability to feel pain and pleasure, joy and sorrow, love and hate are the ends of intelligence not the means.

"That long life in a chip might be as close as we can come to heaven in a universe made of matter and energy and information. It can be heaven or hell in a chip...Bit streams have no more purpose than do the blind genetic pathways of Darwinian evolution."

>>No purpose, no meaning, no intelligent design, no direction, no context, and devoid of creative thought. Pure thought will not create an utopian world.

"Believers may also transfer their belief to a chip's bit stream."

>>What is belief? It is a feeling that something is true, it is an emotion. It is impossible to transfer an emotion to a chip. Chips can only mimck the responses of emotion with puppet strings and gestures. Real emotions in a chip will not exist. Is reality what we think?

"And religion has failed to explain the mechanics of the soul".

>>Science has proven nothing. Faith is not a mechanical recreation. Faith is the substance of things that are true but not seen. True faith, philosophy, and science will cooperate and explain complexity and provide meaning and context. Random convergence of hidden rules will not explain complexity. Instead, it will not be understood and it will be worshipped. Evolutionary science will fail to explain the mechanics of its creations.

"A digital mind has a physical identity because it is a unique pattern in a bit stream."

>>Can a hologram have a soul? Is a hologram aware of his existence? Digital bits have no awareness or identity. If the bit patterns in the stream morph by rules embedded within the data, the digital identity is lost.

"Where is the justice in granting someone infinite pleasure in exchange for finite pain or for finite good deeds or worship?"

>>We learn from experience. Pain is necessary for survival. Remove pain and you won't last a week. Pain drives us to eat and work. Pain is a part of life.

Kosko predicts the future within the framework of a paradigm shift from binary thinking to fuzzy logic. There is an extensive index to allow for easy reference and about 100 pages of footnotes that keep the technical jargon out of the primary text. The story flows like a science fiction novel in which the author is constantly surprising the reader with new insights into the way things may be. A great book that leaves you feeling enlightened and just plain smarter.

There is a lot going on in this book. I'd like to say that it was actually good. But I can't. It was OK. About ten years ago I read an interview of Kosko in the IEEE Spectrum magazine. I was immediately floored by this man's talents: musician, mathematician, scientist, philosopher, you name it, the man had done it. At about the same time, I read Kosko's Fuzzy Thinking. This was at the tail end of a graduate school career, and I enjoyed it very much. The raves from that interview were true. That book opened my mind to a whole new way of approaching math. Recently, I was in the book store, and noticed Kosko's newest book, Noise, on the shelf; I opened it up, skimmed the contents, and remembered what a pleaseure it was to read Fuzzy Thinking so many years ago. I thought I would "catch up" with my Kosko reading before tackling his newest volume. So this is why I bought Heaven in a Chip.

The book is full of ideas.

Unfortunately, many of these ideas read like science fiction, and only a small fraction of them will prove prescient. The appendix is loaded with equations and notes that, I think, would have read better if they were integrated into the main text. The book reads like a stream-of-consciousness at times, with the end-notes tacked on to provide some rigor. Kosko surely knows his stuff.

Being ten years older than when I read Kosko for the first time, I'm much more tuned in to the man's writing ability, his ability to convey ideas in a tight manner, and his grammar and punctuation. Probably due to the success of his previous work (or laziness by the editor) many punctuation errors abound, giving way to choppy sentences and difficult to understand prose. The ideas are there, but they're not tight.

The book is divided into three parts:
Part 1: Fuzzy Politics
Part 2: Fuzzy science
Part 3: Fuzzy Digital Culture

Each part is divided into chapters that give examples of how fuzzy logic can help make a better society, make better technology, or make better government.

In brief, fuzzy logic is the application of the belief that things in the world (and universe) are not just "black and white," but shades of gray. Objects can "be" two apposing properties at once. For example, a person can be both evil and good, to a certain degree, at the same time. Extend this reasoning to math, and then apply it to society, government, and science, and you have the jist of this book.

I don't know where you will find a book quite like this one. Buy it because it's unique, but try not to squirm too much every time Kosko misses a comma.

Kosko hits a home run here. Much better than his Fuzzy Thinking tome.

"The Fuzzy Future" is a wide-ranging work that attempts to integrate concepts from disciplines as diverse as physics, neurophysiology, and the social sciences. It's well-written, but not always easy to follow, due to the diverse subject matter. Definitely not "light reading"!

The way the fuzzy paradigm is introduced and developed is very inspiring for those that come from more traditional ways of thinking. The author makes the transition from classical logic to fuzzy logic in a very clear way. The fields of aplication of fuzzy logic are very well represented in the book. I would stongly support the author to publish a second edition of the book.

I purchased the book for a graduate level engineering course. Perhaps the other raters are orders of magnitude smarter than I, because I found the book to be extremely difficult to understand, almost to the point of laughability. The narrative is unnecessarily complex in my opinion, requiring a serious student to read and reread multiple times until a concept can be grasped. And you better have a dictionary handy because you will likely come across terms that even a well educated person will not recognize. To make matters worse, the text is LOADED with errata. On several occasions I struggled for hours working through examples in various chapters, pulling my hair out and not getting it, only to discover later after confronting the professor that the example was wrong. Not only are there numerical errors laced throughout the text and in the answer appendix, but there are MANY instances where the concept/strategy is not fully explained in an example, leaving you to scratch your head as to why particular variables and their value were chosen (not calculated), why a certain step was performed or not performed, and why certain "tactical decisions" were made as you make your way through a procedure. Several of the sketches are sloppy too where the accompanying narrative does not always match with what the sketch is telling you.
For a rather complex subject, the last thing you need is to struggle with the text. There are so many errors, and so many instances where a complex idea or example is not fully explained that I would recommend purchasing other reference material; at least until the 3rd edition of this text comes out and corrects most of the errata.

Very good book for a solid background on Fuzzy Logic. Highly reccomented. Ross is a very involved author and enthousiastic supporter of Fuzzy logic theory use in problem solving. Try to solve some of the problems in the book. They provide much inside on real applications of the fuzzy logic Theory

If you decide to buy a book on fuzzy logic or applications of fuzzy logic, this is absolutely the best book for introductory level. In other words, this source gives a non-fuzzy and comprehensive knowledge to reader.
I strongly recommend this book to everybody for an exact comprehensive introduction to the theory of Zadeh.

With the exception of Ch. 1, the first part of the book is o.k. To see my problem with chapter 1, simply look at the article on bounded rationality he uses in his discussion of a chess game. First, several parts of the article are coppied word for word directly in his text; I have no problem with this, but they should appear in quotes. Second, I don't think his analysis of the article is accurate.
Ross does an excellent job of introducing binary logic and extending the results to fuzzy logic. However, other than this one chapter, the rest of the rest of the book is not worth the read. A much better book is by Yager and Filev. I went with Ross' text because it was published in 2004 (you know, latest is greatest) compared to the 1995 publishing of Yager's book. Don't make the same mistake, just get Yager's book; you will learn more and save yourself some money!