Blind Equalization in Neural Networks ：Theory, Algorithms and Applications

Publication subTitle ：Theory, Algorithms and Applications

Author： Zhang Liyi;Press Tsinghua University  

Publisher： De Gruyter‎

Publication year： 2017

E-ISBN: 9783110450293

P-ISBN(Paperback): 9783110449624

Subject： TP183 Calculation with Artificial Neural Network

Keyword： Civil engineering, surveying & building,算法理论,计算机软件,计算技术、计算机技术,自动化技术、计算机技术

Language： ENG

Access to resources Favorite

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Description

The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.

Chapter

Preface

Contents

1. Introduction

2. The Fundamental Theory of Neural Network Blind Equalization Algorithm

3. Research of Blind Equalization Algorithms Based on FFNN

4. Research of Blind Equalization Algorithms Based on the FBNN

5. Research of Blind Equalization Algorithms Based on FNN

6. Blind Equalization Algorithm Based on Evolutionary Neural Network

7. Blind equalization Algorithm Based on Wavelet Neural Network

8. Application of Neural Network Blind Equalization Algorithm in Medical Image Processing

Appendix A: Derivation of the Hidden Layer Weight Iterative Formula in the Blind Equalization Algorithm Based on the Complex Three-Layer FFNN

Appendix B: Iterative Formulas Derivation of Complex Blind Equalization Algorithm Based on BRNN

Appendix C: Types of Fuzzy Membership Function

Appendix D: Iterative Formula Derivation of Blind Equalization Algorithm Based on DRFNN

References

Index

The users who browse this book also browse


No browse record.