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Zhang Neural Networks and Neural-Dynamic Method $270.00
Authors: Yunong Zhang and Chenfu Yi (Sun Yat-Sen University, Guangzhou, China) 
Book Description:
The real-time solution to a mathematical problem arises in numerous fields of science, engineering, and business. It is usually an essential part of many solutions, e.g., matrix/vector computation, optimization, control theory, kinematics, signal processing, and
pattern recognition. In recent years, due to the in-depth research on neural networks, numerous recurrent neural networks (RNN) based on the gradient-based method have been developed and investigated. Particularly, some simple neural networks were proposed to
solve linear programming problems in real time and implemented on analog circuits. In this book, ZNN, ZD or ZND theory formalizes these problems and solutions in the time-varying context and provides compact models that could solve those dynamic problems.

Table of Contents:
1 Introduction

I Matrix-Vector Problems

2 ZNN Solving the Time-Varying Linear System A(t)x(t) = b(t)

3 ZNN for Time-Varying Convex Quadratic Optimization

II Pure Matrix Problems

4 ZNN for Time-Varying Matrix Inversion and Pseudoinverse-Solving

5 ZNN for Linear Time-Varying Matrix Equations Solving

6 ZNN for Time-Varying Matrix Square Roots Finding

III Return to Scalar or Constant Problems

7 Zhang Dynamics for the Scalar-Valued Nonlinear Problems

8 ZNN and GNN Models for Linear Constant Problems Solving 198

IV Final Comparisons and Discussions

9 Unified Neural-Network Models 228

10 Conclusions and Outlook


      Mathematics Research Developments
   Binding: ebook
   Pub. Date: 2011
   Pages: 7 x 10
   ISBN: 978-1-61728-465-6
   Status: AV
Status Code Description
AN Announcing
FM Formatting
PP Page Proofs
FP Final Production
EP Editorial Production
PR At Prepress
AP At Press
AV Available
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Zhang Neural Networks and Neural-Dynamic Method