Competition-Based Neural Networks with Robotic Applications



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Éditeur :

Springer


Paru le : 2017-05-30



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Description

Focused on solving competition-based problems, this book designs, proposes, develops, analyzes and simulates various neural network models depicted in centralized and distributed manners. Specifically, it defines four different classes of centralized models for investigating the resultant competition in a group of multiple agents. With regard to distributed competition with limited communication among agents, the book presents the first distributed WTA (Winners Take All) protocol, which it subsequently extends to the distributed coordination control of multiple robots.
Illustrations, tables, and various simulative examples, as well as a healthy mix of plain and professional language, are used to explain the concepts and complex principles involved. Thus, the book provides readers in neurocomputing and robotics with a deeper understanding of the neural network approach to competition-based problem-solving, offers them an accessible introduction to modeling technology and the distributed coordination control of redundant robots, and equips them to use these technologies and approaches to solve concrete scientific and engineering problems.
Pages
121 pages
Collection
n.c
Parution
2017-05-30
Marque
Springer
EAN papier
9789811049460
EAN PDF
9789811049477

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
12
Taille du fichier
14326 Ko
Prix
52,74 €
EAN EPUB
9789811049477

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
12
Taille du fichier
3205 Ko
Prix
52,74 €

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