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NEURAL COMPUTING FOR OPTIMIZATION AND COMBINATORICS
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NEURAL COMPUTING FOR OPTIMIZATION AND COMBINATORICS
A introductory fragment is available
Language of a book: Английский
Publisher: Gardners Books

    Since Hopfield proposed neural network computing for optimization and combinatorics problems, many neural network investigators have been working on optimization problems. In this book a variety of optimization problems and combinatorics problems are presented by respective experts.A very useful reference book for those who want to solve real-world applications, this book contains applications in graph theory, mathematics, stochastic computing including the multiple relaxation, associative memory and control, resource allocation problems, system identification and dynamic control, and job-stop scheduling.Contents:N-Queen and Crossbar ProblemsGate Packing ProblemsMaximum Clique Problems: Part 1Maximum Clique Problems: Part 2Multi-Layer Channel Routing ProblemsJob-Shop SchedulingBIBD ProblemsDiscovering RNA InteractionsMissionaries and Cannibals ProblemsFunctional Link NetsIdentification and ControlRamsey NumbersReadership: Applied scientists, computer scientists and engineers.Key Features:Contains the latest research results in regulatory genomics by experts in this area

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