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7. Blind equalization Algorithm Based on Wavelet Neural Network

  • Liyi Zhang
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Blind Equalization in Neural Networks
This chapter is in the book Blind Equalization in Neural Networks

Abstract

The concept, structure, and characteristics of wavelet neural network are described in this chapter. The basic principle of wavelet neural network blind equalization algorithms is analyzed. Blind equalization algorithm based on three-layer feed-forward wavelet neural network and bilinear feedback wavelet neural network are studied. Iterative formulas are derived for the real and complex system. The effectiveness is verified by computer simulation.

Abstract

The concept, structure, and characteristics of wavelet neural network are described in this chapter. The basic principle of wavelet neural network blind equalization algorithms is analyzed. Blind equalization algorithm based on three-layer feed-forward wavelet neural network and bilinear feedback wavelet neural network are studied. Iterative formulas are derived for the real and complex system. The effectiveness is verified by computer simulation.

Chapters in this book

  1. Frontmatter I
  2. Preface V
  3. Contents VII
  4. 1. Introduction 1
  5. 2. The Fundamental Theory of Neural Network Blind Equalization Algorithm 17
  6. 3. Research of Blind Equalization Algorithms Based on FFNN 51
  7. 4. Research of Blind Equalization Algorithms Based on the FBNN 94
  8. 5. Research of Blind Equalization Algorithms Based on FNN 124
  9. 6. Blind Equalization Algorithm Based on Evolutionary Neural Network 149
  10. 7. Blind equalization Algorithm Based on Wavelet Neural Network 180
  11. 8. Application of Neural Network Blind Equalization Algorithm in Medical Image Processing 205
  12. Appendix A: Derivation of the Hidden Layer Weight Iterative Formula in the Blind Equalization Algorithm Based on the Complex Three-Layer FFNN 229
  13. Appendix B: Iterative Formulas Derivation of Complex Blind Equalization Algorithm Based on BRNN 231
  14. Appendix C: Types of Fuzzy Membership Function 235
  15. Appendix D: Iterative Formula Derivation of Blind Equalization Algorithm Based on DRFNN 239
  16. References 243
  17. Index 251
https://doi.org/10.1515/9783110450293-007

Chapters in this book

  1. Frontmatter I
  2. Preface V
  3. Contents VII
  4. 1. Introduction 1
  5. 2. The Fundamental Theory of Neural Network Blind Equalization Algorithm 17
  6. 3. Research of Blind Equalization Algorithms Based on FFNN 51
  7. 4. Research of Blind Equalization Algorithms Based on the FBNN 94
  8. 5. Research of Blind Equalization Algorithms Based on FNN 124
  9. 6. Blind Equalization Algorithm Based on Evolutionary Neural Network 149
  10. 7. Blind equalization Algorithm Based on Wavelet Neural Network 180
  11. 8. Application of Neural Network Blind Equalization Algorithm in Medical Image Processing 205
  12. Appendix A: Derivation of the Hidden Layer Weight Iterative Formula in the Blind Equalization Algorithm Based on the Complex Three-Layer FFNN 229
  13. Appendix B: Iterative Formulas Derivation of Complex Blind Equalization Algorithm Based on BRNN 231
  14. Appendix C: Types of Fuzzy Membership Function 235
  15. Appendix D: Iterative Formula Derivation of Blind Equalization Algorithm Based on DRFNN 239
  16. References 243
  17. Index 251
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