Advances in Neural Networks – ISNN 2020

Advances in Neural Networks – ISNN 2020
Author: Min Han
Publisher: Springer Nature
Total Pages: 284
Release: 2020-11-28
Genre: Computers
ISBN: 3030642216


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This volume LNCS 12557 constitutes the refereed proceedings of the 17th International Symposium on Neural Networks, ISNN 2020, held in Cairo, Egypt, in December 2020. The 24 papers presented in the two volumes were carefully reviewed and selected from 39 submissions. The papers were organized in topical sections named: optimization algorithms; neurodynamics, complex systems, and chaos; supervised/unsupervised/reinforcement learning/deep learning; models, methods and algorithms; and signal, image and video processing.


Advances in Neural Networks – ISNN 2020
Language: en
Pages: 284
Authors: Min Han
Categories: Computers
Type: BOOK - Published: 2020-11-28 - Publisher: Springer Nature

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This volume LNCS 12557 constitutes the refereed proceedings of the 17th International Symposium on Neural Networks, ISNN 2020, held in Cairo, Egypt, in December
Advanced Models of Neural Networks
Language: en
Pages: 296
Authors: Gerasimos G. Rigatos
Categories: Technology & Engineering
Type: BOOK - Published: 2014-08-27 - Publisher: Springer

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This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced mo
Neural Networks
Language: en
Pages: 511
Authors: Raul Rojas
Categories: Computers
Type: BOOK - Published: 2013-06-29 - Publisher: Springer Science & Business Media

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Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously sc
Static and Dynamic Neural Networks
Language: en
Pages: 752
Authors: Madan Gupta
Categories: Computers
Type: BOOK - Published: 2004-04-05 - Publisher: John Wiley & Sons

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Neuronale Netze haben sich in vielen Bereichen der Informatik und künstlichen Intelligenz, der Robotik, Prozeßsteuerung und Entscheidungsfindung bewährt. Um
Self-Organizing Neural Networks
Language: en
Pages: 289
Authors: Udo Seiffert
Categories: Computers
Type: BOOK - Published: 2013-11-11 - Publisher: Physica

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The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1