Description

Book Synopsis
A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but also to create new techniques and architectures. Provides in-depth coverage of mathematical modeling along with illustrative computer simulation results.

Table of Contents
Mathematical Preliminaries of Neurocomputing.

Architectures and Electronic Implementation of Neural Network Models.

Unconstrained Optimization and Learning Algorithms.

Neural Networks for Linear, Quadratic Programming and Linear Complementarity Problems.

A Neural Network Approach to the On-Line Solution of a System of Linear Algebraic Equations and Related Problems.

Neural Networks for Matrix Algebra Problems.

Neural Networks for Continuous, Nonlinear, Constrained Optimization Problems.

Neural Networks for Estimation, Identification and Prediction.

Neural Networks for Discrete and Combinatorial Optimization Problems.

Appendices.

Subject Index.

Neural Networks for Optimization and Signal

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    A Hardback by Andrzej Cichocki, R. Unbehauen

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      Publisher: Wiley
      Publication Date: Publication Date: 4/14/1993 12:00:00 AM
      ISBN13: 9780471930105, 978-0471930105
      ISBN10: 0471930105
      Also in:
      Digital signal processing (DSP) Image processing Electronics and communications engineering

      Description

      Book Synopsis
      A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but also to create new techniques and architectures. Provides in-depth coverage of mathematical modeling along with illustrative computer simulation results.

      Table of Contents
      Mathematical Preliminaries of Neurocomputing.

      Architectures and Electronic Implementation of Neural Network Models.

      Unconstrained Optimization and Learning Algorithms.

      Neural Networks for Linear, Quadratic Programming and Linear Complementarity Problems.

      A Neural Network Approach to the On-Line Solution of a System of Linear Algebraic Equations and Related Problems.

      Neural Networks for Matrix Algebra Problems.

      Neural Networks for Continuous, Nonlinear, Constrained Optimization Problems.

      Neural Networks for Estimation, Identification and Prediction.

      Neural Networks for Discrete and Combinatorial Optimization Problems.

      Appendices.

      Subject Index.

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