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Blind Equalization in Neural Networks : Theory, Algorithms and Applications.
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin/Boston :
De Gruyter,
2017.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
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| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
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| 020 | |a 9783110450293 | ||
| 020 | |a 3110450291 | ||
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| 049 | |a UAMI | ||
| 100 | 1 | |a Zhang, Liyi. | |
| 245 | 1 | 0 | |a Blind Equalization in Neural Networks : |b Theory, Algorithms and Applications. |
| 260 | |a Berlin/Boston : |b De Gruyter, |c 2017. | ||
| 300 | |a 1 online resource (268 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Intro; 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. | |
| 505 | 8 | |a Appendix A: Derivation of the Hidden Layer Weight Iterative Formula in the Blind Equalization Algorithm Based on the Complex Three-Layer FFNNAppendix 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. | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a 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. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Neural networks (Computer science) |v Congresses. | |
| 650 | 0 | |a Neural networks (Computer science) |x Scientific applications |v Congresses. | |
| 650 | 6 | |a Réseaux neuronaux (Informatique) |v Congrès. | |
| 650 | 6 | |a Réseaux neuronaux (Informatique) |x Applications scientifiques |v Congrès. | |
| 650 | 7 | |a COMPUTERS / Neural Networks. |2 bisacsh | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast | |
| 655 | 7 | |a Conference papers and proceedings |2 fast | |
| 700 | 1 | |a Press, Tsinghua University. | |
| 776 | 0 | 8 | |i Print version: |a Zhang, Liyi. |t Blind Equalization in Neural Networks : Theory, Algorithms and Applications. |d Berlin/Boston : De Gruyter, ©2017 |z 9783110449624 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5158279 |z Texto completo |
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| 938 | |a De Gruyter |b DEGR |n 9783110450293 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL5158279 | ||
| 994 | |a 92 |b IZTAP | ||