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Soft Computing In Systems And Control Technology
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Soft computing is a branch of computing which, unlike hard computing, can deal with uncertain, imprecise and inexact data. The three constituents of soft computing are fuzzy logic-based computing, neurocomputing, and genetic algorithms. Fuzzy logic contributes the capability of approximate reasoning, neurocomputing offers function approximation and learning capabilities, and genetic algorithms provide a methodology for systematic random search and optimization. These three capabilities are combined in a complementary and synergetic fashion. The book presents a cohesive set of contributions dealing with important issues and applications of soft computing in systems and control technology. The contributions include mathematical developments, fresh results, and how-to-do issues. Among the problems studied via neural, fuzzy, neurofuzzy and genetic methodologies are; data fusion; reinforcement learning; approximation properties; multichannel imaging; signal processing; system optimization; gaming; and several forms of control.
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