Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence/Book and Disk by Bart Kosko (PDF)

Description

Written by one of the foremost experts in the field of neural networks, this is the first book to combine the theories and applications or neural networks and fuzzy systems. The book is divided into three sections: Neural Network Theory, Neural Network Applications, and Fuzzy Theory and Applications. It describes how neural networks can be used in applications such as: signal and image processing, function estimation, robotics and control, analog VLSI and optical hardware design; and concludes with a presentation of the new geometric theory of fuzzy sets, systems, and associative memories.

User’s Reviews

Editorial Reviews: From the Publisher An integrated examination of neural networks and fuzzy systems — from the theoretical level of first principles and the applications level of adaptive fuzzy systems in control and signal processing.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐This is a Classic Great book in the field. I had past discussions with the author Bart Kosko. Bart Kosko is brilliant. I have had years of interest in the topic. I was NASA for a decade and met the creator of the discipline of Fuzzy Logic Lotfi Zadeh a genius. I was privileged to have Lotfi Zadeh as guest speaker at a conference I held at NASA. Lotfi Zadeh wrote the forward comment published in the Bart Kosko book. I completed graduate studies in artificial intelligence and used fuzzy logic in a control system at NASA in a 50 foot 6 degree of freedom robotic arm and published the results in IEEE. I am most proud to have known both of these men who are giants in the field.

⭐Good, quality materials.

⭐Excellent book. I keep it on my shelf of reference books. Uses proof structure to show the (complete) lack of handwaving; it was written when fuzzy math was still considered controversial. It covers the subject very thoroughly and is an excellent read for grounding in the subject. The flip side of that is that if it was (just) a reference book it would only need about half the pages. This means that when implementing something you end up skimming a lot of the pages.Pros: Covers the subject matter extremely well.Cons: Nearly requires a degree in mathematics to get the most out of it.I would recommend this to someone looking for a good book on fuzzy math.

⭐Bart’s is legendary known for his contribution to Neural networks and Fuzzy logic. This book though very good, is an advanced level book preferably for a graduate student. Thorough knowledge of Signal analysis and probability would be needed for most part of the book. Advantages of the book is it is, if not the deepest book, on Neural networks and Fuzzy logic, it will surely count as one of the most finest book dealing in the subjects.Disadvantages: I dont know the reason why Bart has included so many theorem proving solutions like proving why BAM(Bilinear Associative memory) works. Though i commend that he has done a fine work with proving the stability of many learning algorithms. I wont recommend this book to a newbie if opting for Neural networks. Introduction to Neural Networks by Zurada ASIN-0314933913 is better off in teaching all the different Algorithms in depth.This book earns a 5 star from me because of the indepth coverage it has on the subjects.

⭐Satisfied

⭐This book is not useful for beginners and others.I dont recommended this book.

⭐Good

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