9786137340165 - biomedical signal processing : soft computing techniques di r. kshirsagar, pravin; g. akojwar, sudhir (9 risultati)

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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book proposes two novel algorithms for function classification and prediction that extends a three layered Feed Forward Neural Network (FFNN) and the standard Generalized Regression Neural Network (GRNN).In this book genetic a…lgorithm(GA) is used inside the particle swarm optimization(PSO) algorithm to bring the worst particle in PSO search space nearer to the food. This helps in faster convergence of PSO algorithm and the possibility of the algorithm to get stuck at the local minima is eliminated.The detailed analysis of results and comparisons show that the proposed algorithms have effectively improved the performance of a neural network as a classifier and predictor and obtained the better accuracy with minimum mean square error than the non optimized neural networks. 160 pp. Englisch.

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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: R. Kshirsagar PravinDr. Pravin R. Kshirsagar, Associate Professor, ETC Department,at GHRECM, Pune (M.S),India.Dr. Sudhir G. Akojwar, Associate Professor, Head, Department of Electronics and Telecommuni…cation Engineering, at Governmen.

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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Biomedical Signal Processing : Soft Computing Techniques | Pravin R. Kshirsagar (u. a.) | Taschenbuch | 160 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786137340165 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[d…ot]de | Anbieter: preigu Print on Demand.

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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book proposes two novel algorithms for function classification and prediction that extends a three layered Feed Forward Neural Network (FFNN) and the standard Generalized Regression Neural Network (GRNN).In this book genetic algor…ithm(GA) is used inside the particle swarm optimization(PSO) algorithm to bring the worst particle in PSO search space nearer to the food. This helps in faster convergence of PSO algorithm and the possibility of the algorithm to get stuck at the local minima is eliminated.The detailed analysis of results and comparisons show that the proposed algorithms have effectively improved the performance of a neural network as a classifier and predictor and obtained the better accuracy with minimum mean square error than the non optimized neural networks.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 160 pp. Englisch.

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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book proposes two novel algorithms for function classification and prediction that extends a three layered Feed Forward Neural Network (FFNN) and the standard Generalized Regression Neural Network (GRNN).In this book genetic algori…thm(GA) is used inside the particle swarm optimization(PSO) algorithm to bring the worst particle in PSO search space nearer to the food. This helps in faster convergence of PSO algorithm and the possibility of the algorithm to get stuck at the local minima is eliminated.The detailed analysis of results and comparisons show that the proposed algorithms have effectively improved the performance of a neural network as a classifier and predictor and obtained the better accuracy with minimum mean square error than the non optimized neural networks.