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[null,"1.","Record Nr.",null,"UNINA9910796608603321"]
[null,null,"Autore",null,"Zhang Liyi"]
[null,null,"Titolo",null,"Blind equalization in neural networks : theory, algorithms and applications / / Liyi Zhang [and three others]"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, [Germany] ; ; Boston, [Massachusetts] : , : De Gruyter : , : Tsinghua University Press, , 2018"]
[{"$nulls":4},"©2018"]
[null,null,"ISBN",null,"3-11-044967-6"]
[null,null,"Descrizione fisica",null,"1 online resource (268 pages) : illustrations"]
[null,null,"Disciplina",null,"006.32"]
[null,null,"Soggetti",null,"Neural networks (Computer science)"]
[{"$nulls":4},"Neural networks (Computer science) - Scientific applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Frontmatter -- 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"]
[null,null,null,"Sommario/riassunto","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."]