
Fuzzy Neural Intelligent Systems
Mathematical Foundation and the Applications in Engineering
CRC Press
1st Edition
Published on 21. September 2000
Book
Hardback
392 pages
978-0-8493-2360-7 (ISBN)
Description
Although fuzzy systems and neural networks are central to the field of soft computing, most research work has focused on the development of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems, especially their mathematical foundations.
Fuzzy Neural Intelligent Systems fills this gap. It develops a mathematical basis for fuzzy neural networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing their focus into three main areas of interest, the authors give a systematic, comprehensive treatment of the relevant concepts and modern practical applications:
Fundamental concepts and theories for fuzzy systems and neural networks.
Foundation for fuzzy neural networks and important related topics
Case examples for neuro-fuzzy systems, fuzzy systems, neural network systems, and fuzzy-neural systems
Suitable for self-study, as a reference, and ideal as a textbook, Fuzzy Neural Intelligent Systems is accessible to students with a basic background in linear algebra and engineering mathematics. Mastering the material in this textbook will prepare students to better understand, design, and implement fuzzy neural systems, develop new applications, and further advance the field.
Fuzzy Neural Intelligent Systems fills this gap. It develops a mathematical basis for fuzzy neural networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing their focus into three main areas of interest, the authors give a systematic, comprehensive treatment of the relevant concepts and modern practical applications:
Fundamental concepts and theories for fuzzy systems and neural networks.
Foundation for fuzzy neural networks and important related topics
Case examples for neuro-fuzzy systems, fuzzy systems, neural network systems, and fuzzy-neural systems
Suitable for self-study, as a reference, and ideal as a textbook, Fuzzy Neural Intelligent Systems is accessible to students with a basic background in linear algebra and engineering mathematics. Mastering the material in this textbook will prepare students to better understand, design, and implement fuzzy neural systems, develop new applications, and further advance the field.
More details
Language
English
Place of publication
Bosa Roca
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Undergraduate
Illustrations
37 s/w Tabellen, 5 s/w Photographien bzw. Rasterbilder
37 Tables, black and white; 5 Halftones, black and white
Dimensions
Height: 260 mm
Width: 183 mm
Thickness: 26 mm
Weight
930 gr
ISBN-13
978-0-8493-2360-7 (9780849323607)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Hongxing Li | C.L. Philip Chen | Han-Pang Huang
Fuzzy Neural Intelligent Systems
Mathematical Foundation and the Applications in Engineering
E-Book
10/2018
CRC Press
€165.99
Available for download

Hongxing Li | C.L. Philip Chen | Han-Pang Huang
Fuzzy Neural Intelligent Systems
Mathematical Foundation and the Applications in Engineering
E-Book
10/2018
CRC Press
€165.99
Available for download
Persons
Hongxing Li, C.L. Philip Chen, Han-Pang Huang
Author
Beijing Normal University, China
San Antonio, Texas, USA
National Taiwan University, Taipei
Content
Foundation of Fuzzy Systems. Determination of Membership Functions. Mathematical Essence and Structures of Feedforward Artificial Neural Networks. Functional-Link Neural Networks and Visualization Means of Some Mathematical Methods. Flat Neural Networks and Rapid Learning Algorithms. Basic Structure of Fuzzy Neural Networks. Mathematical Essence and Structures of Feedback Neural Networks and Weight Matrix Design. Generalized Additive Multifactorial Function and Its Applications to Fuzzy Inference and Neural Networks. The Interpolation Mechanism of Fuzzy Control. The Relationship between Fuzzy Controllers and PID Controllers. Adaptive Fuzzy Controllers Based on Variable Universes. The Basics of Factor Spaces. Neuron Models Based on Factor Spaces Theory and Factor Space Canes. Foundation of Neuro-Fuzzy Systems and an Engineering Application. Data Preprocessing. Control of a Flexible Robot Arm Using a Simplified Fuzzy Controller. Application of Neuro-Fuzzy Systems: Development of a Fuzzy Learning Decision Tree and Application to Tactile Recognition. Fuzzy Assessment Systems of Rehabilitative Process for CVA Patients. A DSP-Based Neural Controller for a Multi-Degree Prosthetic Hand. Index.