Детальная информация

Название: Competition-based neural networks with robotic applications
Авторы: Shuai Li; Long Jin
Выходные сведения: Singapore: Springer, 2017
Коллекция: Электронные книги зарубежных издательств; Общая коллекция
Тематика: Нейронные сети; Робототехнические системы; neural networks; robotic systems
УДК: 621.865.8; 004.032.26
Тип документа: Другой
Тип файла: Другой
Язык: Английский
Права доступа: Доступ по паролю из сети Интернет (чтение, печать)
Ключ записи: RU\SPSTU\edoc\60670

Разрешенные действия: Посмотреть

Аннотация

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.

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