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Choosing Neural Equalizers Using Genetic Algorithm: An approach to search for the neural network structure - Softcover
Synopsis
Genetic Algorithm and Artificial Neural Networks have been combined to solve several problems in last two decades. The first one have been used to help find parameters and topology decision of the second one, or to cope with learning algorithm limitations. Some problems demand the application of neural networks as alternative solution to solve them, but studies that develop a methodology to indicate the best neural architecture suitable for a specific application is rare to be found in the literature. In this work we apply genetic algorithm to search for neural weights and use this information to indicate the best structure and measure the efficiency of the learning algorithm. We used a channel equalization problem as an example to test the proposed methodology. The results obtained from this application are very promising.
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Choosing Neural Equalizers Using Genetic Algorithm
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LAP LAMBERT Academic Publishing Jan 2015, 2015
ISBN 10: 3659673536
ISBN 13: 9783659673535
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Genetic Algorithm and Artificial Neural Networks have been combined to solve several problems in last two decades. The first one have been used to help find parameters and topology decision of the second one, or to cope with learning algorithm limitations. Some problems demand the application of neural networks as alternative solution to solve them, but studies that develop a methodology to indicate the best neural architecture suitable for a specific application is rare to be found in the literature. In this work we apply genetic algorithm to search for neural weights and use this information to indicate the best structure and measure the efficiency of the learning algorithm. We used a channel equalization problem as an example to test the proposed methodology. The results obtained from this application are very promising. 56 pp. Englisch. Seller Inventory # 9783659673535
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Choosing Neural Equalizers Using Genetic Algorithm : An approach to search for the neural network structure
Published by
LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659673536
ISBN 13: 9783659673535
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Genetic Algorithm and Artificial Neural Networks have been combined to solve several problems in last two decades. The first one have been used to help find parameters and topology decision of the second one, or to cope with learning algorithm limitations. Some problems demand the application of neural networks as alternative solution to solve them, but studies that develop a methodology to indicate the best neural architecture suitable for a specific application is rare to be found in the literature. In this work we apply genetic algorithm to search for neural weights and use this information to indicate the best structure and measure the efficiency of the learning algorithm. We used a channel equalization problem as an example to test the proposed methodology. The results obtained from this application are very promising. Seller Inventory # 9783659673535
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Choosing Neural Equalizers Using Genetic Algorithm
Published by
LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659673536
ISBN 13: 9783659673535
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Softcover
Seller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mota TiagoTiago Mota received the B.Sc. degree in electrical engineering from the Federal University of Bahia, Brazil, in 2003, the M.Sc. degree from the Federal University of Bahia in 2014. From 2003 to 2008, he was a Mobile Telecom. Seller Inventory # 5171487
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Choosing Neural Equalizers Using Genetic Algorithm
Published by
LAP LAMBERT Academic Publishing Jan 2015, 2015
ISBN 10: 3659673536
ISBN 13: 9783659673535
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Genetic Algorithm and Artificial Neural Networks have been combined to solve several problems in last two decades. The first one have been used to help find parameters and topology decision of the second one, or to cope with learning algorithm limitations. Some problems demand the application of neural networks as alternative solution to solve them, but studies that develop a methodology to indicate the best neural architecture suitable for a specific application is rare to be found in the literature. In this work we apply genetic algorithm to search for neural weights and use this information to indicate the best structure and measure the efficiency of the learning algorithm. We used a channel equalization problem as an example to test the proposed methodology. The results obtained from this application are very promising.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch. Seller Inventory # 9783659673535
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Choosing Neural Equalizers Using Genetic Algorithm | An approach to search for the neural network structure
Published by
LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659673536
ISBN 13: 9783659673535
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Taschenbuch
Seller: preigu, Osnabrück, Germany
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Taschenbuch. Condition: Neu. Choosing Neural Equalizers Using Genetic Algorithm | An approach to search for the neural network structure | Tiago Mota (u. a.) | Taschenbuch | 56 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659673535 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 104936178