Fuzzy Logic for Embedded Systems Applications (Embedded Technology) (Paperback)

by Ahmad Ibrahim (Author) "A system whose principal function is not computational but is controlled by a computational system embedded within it is referred to as a computational embedded..." (more)
Key Phrases: bounded difference operation, basic neuron model, fuzzy processor, New York, Example Let, International Conference (more...)

Editorial Reviews

Book Description
Extensive coverage of both the theory and application of fuzzy logic design.

Product Description
Fuzzy Logic for Embedded Systems Applications, by a recognized expert in the field, covers all the basic theory relevant to electronics design, with particular emphasis on embedded systems, and shows how the techniques can be applied to shorten design cycles and handle logic problems that are tough to solve using conventional linear techniques. All the latest advances in the field aree discussed and practical circuit design examples presented.

Fuzzy logic has been found to be particularly suitable for many embedded control applications. The intuitive nature of the fuzzy-based system design saves engineers time and reduces costs by shortening product development cycles and making system maintenance and adjustments easier. Yet despite its wide acceptance—and perhaps because of its name—it is still misunderstood and feared by many engineers. There is a need for embedded systems designers—both hardware and software—to get up to speed on the principles and applications of fuzzy logic in order to ascertain when and how to use them appropriately.

Fuzzy Logic for Embedded Systems Applications provides practical guidelines for designing electronic circuits and devices for embedded systems using fuzzy-based logic. It covers both theory and applications with design examples.

* Unified approach to fuzzy electronics from an engineering point of view
* Easy to follow with plenty of examples
* Review and evaluation of free resources

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Product Details

• Paperback: 312 pages
• Publisher: Newnes (October 10, 2003)
• Language: English
• ISBN-10: 0750676051
• ISBN-13: 978-0750676052
• Product Dimensions: 9.1 x 6.9 x 0.7 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 3.2 out of 5 stars See all reviews (5 customer reviews)
• Amazon.com Sales Rank: #1,907,976 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

2 of 2 people found the following review helpful:

3.0 out of 5 stars Good but many errors, January 23, 2004

By	Montri Tangjarukij (Samutprakarn Thailand) - See all my reviews (REAL NAME)

Good introduction about fuzzy logic plus a ton of web resources. I gave it 3 stars because so many wording errors in this book.

1 of 1 people found the following review helpful:

2.0 out of 5 stars Too much padding, too many typos, September 7, 2004

By	Cdh Manning "Embedded Janitor" (NZ) - See all my reviews (REAL NAME)

While this book does provide a reasonable overview, I found it rather disappointing.

It has too many errors. With highly technical material, it is imperative that the information is correct or else you can't trust it. For example a minus instead of a plus does not help when explaining terminology.

Only half the book is really about fuzzy logic. There is far too much padding eg. 1.large diagrams showing Moore's Law and the layers in an IC gate. These are not subjects that should be covered in a book on fuzzy logic and one is forced to conclude that the author had a page quota to be reached and did it by adding these secions and large verbose reference sections.

A worked example or an appendix showing an algorithm in C would have been far more useful.

1.0 out of 5 stars Misleading Title, March 28, 2008

By	Greg Roberts (San Diego CA, USA) - See all my reviews

"A First Look at Fuzzy Logic and Neural Networks..." might be a lot more accurate. It does a good job of covering the concepts. What it doesn't do is address any of the issues of implementing a fuzzy system in an embedded environment. If you don't know what a fuzzy set is then you should consider this book. If you want some tips or ideas for creating an inference engine for an 8 or 16 bit processor I suggest you look elsewhere.