A high order neural network to solve crossbar switch problem

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6444 LNCS, Issue PART 2, 2010, Pages 692-699

  Ding, Yuxin ^a   Dong, Li ^a   Wang, Ling ^a   Wu, Guohua ^b  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

constraint satisfaction; crossbar switch problem; Hopfield network

Indexed keywords

APPROXIMATION PROPERTIES; COMBINATORIAL OPTIMIZATION PROBLEMS; CONSTRAINT SATISFACTION; CONSTRUCTION METHOD; CONVERGENCE SPEED; CROSSBAR SWITCH; DISCRETE HOPFIELD NETWORKS; DISCRETE HOPFIELD NEURAL NETWORKS; ENERGY FUNCTIONS; ENGINEERING OPTIMIZATION PROBLEMS; FASTER CONVERGENCE; HIGH ORDER; HIGH-ORDER NEURAL NETWORK; HOPFIELD NETWORKS; LOCAL MINIMUMS; NEURAL COMPUTING; NP COMPLETE PROBLEMS;

COMBINATORIAL OPTIMIZATION; COMPUTATIONAL COMPLEXITY; CROSSBAR EQUIPMENT; DATA PROCESSING; HOPFIELD NEURAL NETWORKS; SWITCHING CIRCUITS; SWITCHING NETWORKS; CONSTRAINT SATISFACTION PROBLEMS; NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS; OPTIMIZATION;

NEURAL NETWORKS; PROBLEM SOLVING;

EID: 78650201021     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-17534-3_85     Document Type: Conference Paper

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