Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives at Meripustak

Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives

Books from same Author: Sandberg

Books from same Publisher: John Wiley And Sons

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  • General Information  
    Author(s)Sandberg
    PublisherJohn Wiley And Sons
    ISBN9780471349112
    Pages312
    BindingHardbound
    LanguageEnglish
    Publish YearFebruary 2001

    Description

    John Wiley And Sons Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives by Sandberg

    The first truly up-to-date look at the theory and capabilities of nonlinear dynamical systems that take the form of feedforward neural network structures Considered one of the most important types of structures in the study of neural networks and neural-like networks, feedforward networks incorporating dynamical elements have important properties and are of use in many applications. Specializing in experiential knowledge, a neural network stores and expands its knowledge base via strikingly human routes-through a learning process and information storage involving interconnection strengths known as synaptic weights. In Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives, six leading authorities describe recent contributions to the development of an analytical basis for the understanding and use of nonlinear dynamical systems of the feedforward type, especially in the areas of control, signal processing, and time series analysis. Moving from an introductory discussion of the different aspects of feedforward neural networks, the book then addresses: Classification problems and the related problem of approximating dynamic nonlinear input-output maps The development of robust controllers and filters The capability of neural networks to approximate functions and dynamic systems wit.