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Competition-based neural networks wi...

Li, Shuai.

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Competition-based neural networks with robotic applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Competition-based neural networks with robotic applications/ by Shuai Li, Long Jin.
Author:	Li, Shuai.
other author:	Jin, Long.
Published:	Singapore :Springer Singapore : : 2018.,
Description:	xv, 121 p. :ill., digital ;24 cm.
[NT 15003449]:	Competition Aided with Discrete -- Time Dynamic Feedback -- Competition Aided with Continuous -- Time Nonlinear Model -- Competition Aided with Finite -- time Neural Network -- Competition based on Selective Positive-negative Feedback -- Distributed Competition in Dynamic Networks -- Competition-based Distributed Coordination Control of Robots.
Contained By:	Springer eBooks
Subject:	Neural networks (Computer science) -
Online resource:	http://dx.doi.org/10.1007/978-981-10-4947-7
ISBN:	9789811049477

Competition-based neural networks with robotic applications
Li, Shuai.

Competition-based neural networks with robotic applications[electronic resource] /by Shuai Li, Long Jin. - Singapore :Springer Singapore :2018. - xv, 121 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-530X. - SpringerBriefs in applied sciences and technology..

Competition Aided with Discrete -- Time Dynamic Feedback -- Competition Aided with Continuous -- Time Nonlinear Model -- Competition Aided with Finite -- time Neural Network -- Competition based on Selective Positive-negative Feedback -- Distributed Competition in Dynamic Networks -- Competition-based Distributed Coordination Control of Robots.

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.

ISBN: 9789811049477

Standard No.: 10.1007/978-981-10-4947-7doiSubjects--Topical Terms:

532070
Neural networks (Computer science)

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

Competition-based neural networks with robotic applications
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100 1 $a Li, Shuai. $3 3170629
245 1 0 $a Competition-based neural networks with robotic applications $h [electronic resource] / $c by Shuai Li, Long Jin.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2018.
300 $a xv, 121 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in applied sciences and technology, $x 2191-530X
505 0 $a Competition Aided with Discrete -- Time Dynamic Feedback -- Competition Aided with Continuous -- Time Nonlinear Model -- Competition Aided with Finite -- time Neural Network -- Competition based on Selective Positive-negative Feedback -- Distributed Competition in Dynamic Networks -- Competition-based Distributed Coordination Control of Robots.
520 $a 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.
650 0 $a Neural networks (Computer science) $3 532070
650 0 $a Robotics. $3 519753
650 1 4 $a Engineering. $3 586835
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Robotics and Automation. $3 1066695
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Mathematical Models of Cognitive Processes and Neural Networks. $3 1619875
700 1 $a Jin, Long. $3 3185757
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in applied sciences and technology. $3 1565541
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-4947-7
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