Fuzzy-Logic Books

Fuzzy logic results from probable classifications. Fuzzy logic is about classification. Words are used to build context. Machines must follow rules that humans find intuitive. For example what is an oval. A person can be shown a few examples of an oval and know instinctive which shapes are oval. Fuzzy rules, such as, convex, continueous, closed, etc, probabilities must pattern match to product an action that confirms the object is oval.

Mycin is an expert system with both an inference engine and a knowledge base engine. Mycin uses a fuzzy logic inference engine and derives a best solution through a series of questions and answers. In the 1970's Mycin was used to advise physicians on the treatment of bacterial infections of the blood and meningitis. Mycin uses information about specific symptons and the outcomes of laboratory tests then recommends a certain course of antibotics. The system outputs sentences but the user inputs words. Mycin asks facts about a specific patient. The inference engine has a series of rules and each rule has an action. When a rule is activated the pattern part matches the database. If a pattern match occurs an action results. More questions can result from actions, a backward chaining expert system.

I enjoyed the approach here. The author uses simple, rather concrete examples that allow one to see how fuzzy logic systems work. With the shareware given here it also shows that such systems don't take a lot to construct or work with. As one reviewer says the book doesn't have much on the mathematical theory behind fuzzy logic systems, but the author meants such as a practical approach. And the mathematical theory definitely works as much too much to explain in a work like this. Additionally, the main advantage of using fuzzy systems works as that you don't have to use so much math and bury everything in equations and cryptic symbols. This sort of example makes it easier to see this and work with it.
The knowledge builder shows some ideas as to how one can generate if-then rules in a simple fashion. The decision maker makes the program practically. And the fuzzy cognitive map shows you how fuzzy logic systems can apply to scientific modeling easily.

Not a bad intro to Fuzzy if you know nothing about it and the few real world examples showed me that Fuzzy Logic can be used successfully. But the work the authors have you do with the shareware is too difficult to follow. The results often didn't match up to the book's section and i was left confused. This book is very light in fuzzy theory and left me without knowing how to use fuzzy logic in the real world.

If you're interested in an overview of the subject of fuzzy logic this book may be adequate for your need. It is primarily a manual on how to use the shareware version of the software which is provided. I found this book inadequate in explaining the theory behind fuzzy logic

Nothing is more fascinating than to follow a lively mind poking about for curiosities. And nobody had a livelier mind than Martin Gardner.

The Oklahoma philosopher played with ideas as varied as the background to Lewis Carroll and mathematical games and brain-teasers.

Other writers, too, have been interested in "Alice in Wonderland" and in brainteasers. Gardner was a unique national asset because of the effort he expended on cranks.

For many years, a main outlet for his inquiries was Skeptical Inquirer magazine, the journal of what used to be the Center for the Scientific Investigation of the Paranormal and is now just PSICOP. Sixteen of his "Notes of a Fringe-Watcher" columns are reprinted in "Weird Water & Fuzzy Logic," along with almost 50 book reviews.

He gives most attention to repressed memory therapy and false memory syndrome.

The explosion of claims by adults that they were sexually abused as children is called "the greatest scandal of the century in American psychology." Gardner does not deny that there are many case of unreported child sexual abuse -- who would dare? -- but he does contend that these cases are hidden, not forgotten.

His book was written well before the revelations of sexual abuse by Roman Catholic priests. What we learned from that tends to confirm Gardner's opinion.

Already, he wrote, a vast industry of memory creators was at work. It includes -- it is with us yet -- therapists, most with dubious or non-existent credentials; gullible cops and social workers; and prosecutors run amok. Gardner does not say so, but in some of the worst witchhunts, it seems pretty clear that prosecutors pushing these cases were deranged.

What else can explain going to court with cases of horrible physical assaults that children describe, but which leave not a mark on their bodies?

The claims of the people who believe these wild tales are not noted for the rigor of their evidence, and the repressed memory people are heavily cross-fertilized with believers in alien abductions and satanic cults, for which evidence is equally lacking.

Hundreds of people already have been imprisoned by these witchhunts and more hundreds have had their lives ruined.

A lot of what Gardner writes about is more goofy than anything else, but false memory syndrome is another matter altogether. In recommending Lawrence Wright's book "Remembering Satan," which recounts a monstrous Washington case, Gardner states solemnly: "It is a book every American should read. Someday you may be called for jury duty on a repressed-memory case that can result in terrible injustice unless you and your fellow-jurors are adequately informed."

Usually, however, Gardner is involved in realms where the looniness is comparatively harmless. These include a famous case in which scads of Ph.D.s in mathematics made fools of themselves over a fairly simple problem in logic, Margaret Mead's humbug in Samoa and a collection of scientific blunders in novels.

The blunders are original compilations by Gardner; many of the other columns are simply charmingly retold exposes done by others, such as Derek Freeman's destruction of Mead's reputation.

For those who delighted in these pieces in Skeptical Inquirer, the book version is even better, because it includes the responses of the wounded and bellowing pedagogues whom Gardner has skewered.

One was set off by his review in Book World magazine of a life of Joseph Campbell, who is revealed as a sap and an anti-Semite. The bellows of the Campbellites were loud indeed.

Few of us would ever have heard of Campbell, a shabby pretender, if it had not been for the drumbeating on public television by that ignorant hedge-preacher Billy D. Moyers. Gardner uncharacteristically passes up a chance to heave a harpoon into Moyers' sleek hide.

Too bad. That would have generated more letters and more fun.

Fantastic book, nearly ever essay a clear and brillant piece attacking superstition and blatant pseudoscience

The positive emphasis of this compilation - that any and all claims are best meticulously and exactingly examined in an organized manner - is disappointingly marred by Martin Gardner's shallow knowledge and research of the topics he seeks to debunk.

There is a bit of unintended humor in the preface: "This book is essentially self-contained. The only thing it requires is familiarity...with the basics of general topology, measure theory, and functional analysis, as well as the elements of set theory..."

He says the target is the beginning graduate. I would place it better as a 2nd-year grad course. The text is dense and moves fast. Readability is pretty low. He never introduces a topic with context or overview. Extensive references to the literature were deliberately left out, which I think is wrong since it is a textbook. On the plus side, it is sprinkled with many exercises. (BTW, this is one of those cases that make you wish Springer didn't make authors do their own typesetting.)

There are only three common texts for descriptive set theory: Kechris, Jech, and Moschovakis. Jech has less detail on Polish spaces, Borel sets, and co-analytic sets, so it is not really a substitute, but its conciseness is nice and it makes a good companion. Moschovakis was a big deal when it came out because it collected a lot of information for the first time. But I don't think it is so good in content or style that you should be concerned if you have only Kechris and Jech.

A truly outstanding reference for the purely classical aspects of descriptive set theory, it falls under Kelley's label, "What every young set theorist needs to know." It is not an easy book for the beginner as it is very concise and gives little motivation, but for the advanced student it is essential.

As a Ph.D. student in the field, hardly a day goes by where I don't look up something in this book. I'm buying a new copy since my old one is falling apart.

This is a great book for a control engineer, not someone who wants to learn about fuzzy logic (and the author makes that clear). It has real engineering examples, and a very clear introduction to the area. Also, it covers all the major topics, has lots of examples and code that are very helpful (in matlab). I highly recommend it.... for the engineer who wants to really get a fuzzy controller working - or for someone new to the area (e.g. students who have already had a course on control systems. Chapter 2 is an especially helpful and clear tutorial... You must, however, understand signals and systems, and differential equations...

The only advantage of the book is the software examples available on author's homepage. It say little on the reasoning of fuzzy inference and the basic operations of fuzzy set. If you want to have a complete know-how guide for fuzzy control, you probably be disappointed. You would gain the maximum if your have learnt the basics from other books before dipping into its software examples. In summary, the book is not the functional part for learning fuzzy control.

Grint's general approach is given in a sort of mission statement in the introduction. The book is written for those people who find current management orthodoxies to be inadequate and who are interested in alternative ideas. They should be interested in how these might be applied to management practice; but they will not want "theoretical books about theory". He seems envisage this constituency as being the classic MBA-type student, who is at the same time a practicing manager. Thus Grint's aim is to provide a bridging work between the worlds of academia and practical management. The book is not written as a practical manual of management. A number of real-life examples from the literature are briefly described to illustrate the points; but there are no case studies, or anecdotes based on Grint's experience (he is a career academic). The approach is academic, though the tone is light. The content is best described as suggestive, rather than comprehensive.

First Grint introduces the idea of `fuzzy thinking', based on work in set theory and mathematical logic. The idea that this is the most appropriate type of thinking for real-world management problems is the primary message of the book. Grint goes on to look at change programmes, chaos and evolutionary theory, actor-network theory, leadership and appraisal, risk management, and negotiating theory. In each case he applies his fuzzy thinking perspective.

Grint, though by no means providing a manual of managing under uncertainty, does add a dose of realism not found in many popular management texts on the one hand, or academic literature on the other. Furthermore, some of his suggestions are consistent with recent developments in management theory and practice, implying that the book indirectly has value for the practising manager at the level of its specific discussions.

Grint's general approach is given in a sort of mission statement in the introduction. The book is written for those people who find current management orthodoxies to be inadequate and who are interested in alternative ideas. They should be interested in how these might be applied to management practice; but they will not want "theoretical books about theory". He seems envisage this constituency as being the classic MBA-type student, who is at the same time a practicing manager. Thus Grint's aim is to provide a bridging work between the worlds of academia and practical management. The book is not written as a practical manual of management. A number of real-life examples from the literature are briefly described to illustrate the points; but there are no case studies, or anecdotes based on Grint's experience (he is a career academic). The approach is academic, though the tone is light. The content is best described as suggestive, rather than comprehensive.

First Grint introduces the idea of `fuzzy thinking', based on work in set theory and mathematical logic. The idea that this is the most appropriate type of thinking for real-world management problems is the primary message of the book. Grint goes on to look at change programmes, chaos and evolutionary theory, actor-network theory, leadership and appraisal, risk management, and negotiating theory. In each case he applies his fuzzy thinking perspective.

Grint, though by no means providing a manual of managing under uncertainty, does add a dose of realism not found in many popular management texts on the one hand, or academic literature on the other. Furthermore, some of his suggestions are consistent with recent developments in management theory and practice, implying that the book indirectly has value for the practising manager at the level of its specific discussions.

The C++ source code that ships with this book, makes it already worth the buy. Combined with this, the book has some good practical examples of real world fuzzy systems

After Bart Kosko's "Fuzzy Thinking," this was the first fuzzy logic book that I bought. The writer's prose is readable and understandable and the explanations of fuzzy logic, especially as applied to modelling, are quite good. My criticism is that the source code provided is not truly in C++; very few (and no important) C++ features are utilized. With very little change, the examples could be compiled with a C compiler. This is most unfortunate, since fuzzy logic in general, and the modelling system described are excellent for object-oriented software. I hope that the 1998 edition of the book does better.

I found this book very useful. Especially the case studies presnted in the text.

'+ 've pts
1 ]The book gives an indepth treatment of the topic.
'- 've pts
I just hope for 2 thigs:
1 ] The book shld have got an appendix giving more info on the back ground needed for some of the key concepts covered in the same.
2 ] The book shld have got more links to web sites related to the topic.

As the other reviewer said, if you know nothing about neural networks, then this is a good place to start. It begins with an overview of neural networks in the brain, using the visual processing system as a detailed example. Once this is done, it moves on to general concepts and basic theory encountered in the field. The drawback is topics tend to be skimmed over with the minimum of detail and very few examples, some of which are barely explained - often there are figures of networks with no real discussion of what is going on. Having said that, reading this book gave me enough understanding of the underlying ideas so that i was able to pick up a more mathematical treatment of the subject and follow what was going on and i definitely think it was worth the purchase.

If you have no idea what this subject is all about or if you are interested in knowing the concept of neural networks then try this book, it gives you the conceptual view in a simple matter which is perfectly enough to gain your interest in the subject. If any one wanna work in this field I strongly suggest them to read this book before they want to continue in the field.

"A simple and well organised matter" is the best fit for this book.

Fuzzy topology, Quasi-uniforms spaces, ordered spaces

Despite being used for decades controlling safety/time-critical non-linear manufacturing processes (and other applications), the neural networks/AI label evokes images from science fiction by the general media. Beyond the initially intimidating title, this book is of real use to researchers addressing complex problems, and those trying to use neural networks. Without resorting to hardwired neural networks, or MATLAB with neural networks toolbox, one can readily understand and use the included (dated now) C++ neural network code (C compiler excluded- but use Borland/Microsoft).

The basic neural network steps include: model process (e.g. manufacturing), gather data, pre-process data, compile, link & run the neural network code, let it iterate & learn, analyse output data sets, then use to hard-code a PID-controller (say). Even a 486-66/Win3.1/16MB RAM CPU can readily handle 25 variable/1000+ data point (pultrusion) manufacturing process (1994). As I often tend to use fuzzy-pre processing, and C/C++ for hacking demonstrators, the combined treatment of fuzzy logic, C++ and neural networks works very well.

Topics include: fuzzy logic introduction, constructing a neural network, C++ and object orientation, models and Adaptive Resonance Theory (ART), learning, self organization & resonance, backpropogation and non-linear optimization, Bidirectional Associative Memory (BAM), Fuzzy Associative Memory (FAM), and applications for financial modelling.

Weaknesses include: the now dated and programming-novice unfriendly software, and the ultimately limited software- far better when you are experienced to use MATLAB with neural networks toolbox for developing fast, usable networks.

Overall, the style is approachable, and the content readily understandable and usable by the typical professional engineer/graduate engineering student audience. This book includes much helpful annotated pseudo-code, examples, references, defined terms, and mathematical explanations.