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Titlebook: Advances in Neural Networks – ISNN 2012; 9th International Sy Jun Wang,Gary G. Yen,Marios M. Polycarpou Conference proceedings 2012 Springe

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Samantha Shepherd,Sarah McMahonel parameters. We demonstrate the efficiency of the new method using the artificial signals, which are random mixtures of horizontal and vertical bars that are a benchmark for Boolean factor analysis. Then we show that the method can be used for real task solving when analyzing data from the Kyoto Encyclopedia of Genes and Genomes.
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M. Joseph Sirgy,Rhonda Phillips,Don Rahtzdifference rules. Computer-simulation and numerical results demonstrate the efficacy and accuracy of the presented continuous-time ZNN model and the proposed discrete-time ZNN algorithms for solving online time-varying QP problems.
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Conference proceedings 2012henyang, China, in July 2012. The 147 revised full papers presented were carefully reviewed and selected from numerous submissions. The contributions are structured in topical sections on mathematical modeling; neurodynamics; cognitive neuroscience; learning algorithms; optimization; pattern recogni
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Conference proceedings 2012are structured in topical sections on mathematical modeling; neurodynamics; cognitive neuroscience; learning algorithms; optimization; pattern recognition; vision; image processing; information processing; neurocontrol; and novel applications.
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M. Joseph Sirgy,Rhonda Phillips,Don R. Rahtze developed procedures that efficiently compute local Lipschitz constants over subsets of the weight space. Those Local Lipschitz constants can be used to compute lower bounds on the optimal solution.
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M. Joseph Sirgy,Rhonda Phillips,Don R. Rahtze coefficients of polynomial (connection weight). The performance of the proposed model are illustrated with by using two kinds of representative numerical dataset such as Automobile Miles per Gallon, (MPG dataset) and Boston Housing dataset and their results are compared with those reported in the previous studies.
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