Fuzzy Neural Intelligent Systems: Mathematical Foundation and the Applications in Engineering

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CRC Press, Sep 21, 2000 - Computers - 392 pages
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.
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    Foundation of Fuzzy Systems
    Determination of Membership Functions
    Mathematical Essence and Structures of Feedforward Artificial Neural Networks
    Functionallink 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 Weighted Multifactorial Function and its Applications to Fuzzy Inference and Neural Networks
    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 NeuroFuzzy Systems and an Engineering Application
    Data Preprocessing
    Control of a Flexible Robot Arm using a Simplified Fuzzy Controller
    Application of NeuroFuzzy Systems Development of a Fuzzy Learning Decision Tree and Application to Tactile Recognition
    Fuzzy Assessment Systems of Rehabilitative Process for CVA Patients

    The Interpolation Mechanism of Fuzzy Control
    The Relationship between Fuzzy Controllers and PID Controllers
    A DSPbased Neural Controller for a Multidegree Prosthetic Hand

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