Fuzzy Neural Intelligent Systems: Mathematical Foundation and the Applications in EngineeringAlthough 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. 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. |
From inside the book
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... defined as a combination of fuzzy systems and neural networks such that the parameters of fuzzy systems are determined by neural network learning algorithms . The intention is to take the advantage of neural network methods to improve ...
... Definition of Factor Spaces , 203 12.5 A Note on The Definition of Factor Spaces , 204 12.6 Concept Description in a Factor Space , 205 12.7 The Projection and Cylindrical Extension of the Representation Extension , 207 12.8 Some ...
... defined by the concepts . The extension of the concept " set " has been interpreted as the set formed by all of the objects defined by the concept . That is , sets can be used to express concepts . Since set operations and ...
... define a man as baldheaded because one cannot establish an absolute boundary by means of the number of hairs . But the tiny increase or decrease in the number of hairs ( changes in quantity ) does influence the change in quality , which ...
... defined as follows : μA ( U ) 0 0.2 0.2 0.6 0.9 1.0 0.9 0.9 0.6 0.2 0 Ա 1 2 3 4 5 6 7 8 9 Example 3 Let U be the set of real numbers and A be the set of " real numbers considerably larger than 10 " . Then a membership function of A is ...
Contents
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23 | |
Mathematical Essence and Structures of Feedforward Artificial Neural Networks | 47 |
Functionallink Neural Networks and Visualization Means of Some Mathematical Methods | 72 |
Flat Neural Networks and Rapid Learning Algorithms | 90 |
Basic Structure of Fuzzy Neural Networks | 113 |
Mathematical Essence and Structures of Feedback Neural Networks and Weight Matrix Design | 126 |
Generalized Additive Weighted Multifactorial Function and its Applications to Fuzzy Inference and Neural Networks | 140 |
Adaptive Fuzzy Controllers Based on Variable Universes | 181 |
The Basics of Factor Spaces | 197 |
Neuron Models Based on Factor Spaces Theory and Factor Space Canes | 219 |
Foundation of NeuroFuzzy Systems and an Engineering Application | 241 |
Data Preprocessing | 255 |
Control of a Flexible Robot Arm using a Simplified Fuzzy Controller | 267 |
Application of NeuroFuzzy Systems Development of a Fuzzy Learning Decision Tree and Application to Tactile Recognition | 295 |
Fuzzy Assessment Systems of Rehabilitative Process for CVA Patients | 322 |
The Interpolation Mechanism of Fuzzy Control | 152 |
The Relationship between Fuzzy Controllers and PID Controllers | 165 |
A DSPbased Neural Controller for a Multidegree Prosthetic Hand | 351 |
Other editions - View all
Fuzzy Neural Intelligent Systems: Mathematical Foundation and the ... Hongxing Li,C.L. Philip Chen,Han-Pang Huang No preview available - 2000 |