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Condizione: New. pp. 172.

Taschenbuch. Condizione: Neu. System Identification Of Nonlinear Chaotic Signals | Using Neural Network Approach | Sagar Dhoble | Taschenbuch | 172 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659358746 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural network, which is smaller, faster and with a better generalization performance. This book is my effort to mainly showcase the capability of time series prediction using neural network approach to predict complex Nonlinear datasets for forecasting. Experiments were carried out on Netflow series. It is observed that these problems exhibit a rich chaotic behavior and also leads to strange attractor. Multi-step ahead predictions have been carried out and the proposed neural network models have been optimized. 172 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dhoble SagarBorn in India(Yavatmal) in 1987, Mr. Sagar Dhoble completed Bachelor of Engineer in Electronics and Telecommunication at Amaravati University in 2009. After graduation I joined Tata Teleservices Limited as BSS Engineer in.

Condizione: New. Print on Demand pp. 172 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 172.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural network, which is smaller, faster and with a better generalization performance. This book is my effort to mainly showcase the capability of time series prediction using neural network approach to predict complex Nonlinear datasets for forecasting. Experiments were carried out on Netflow series. It is observed that these problems exhibit a rich chaotic behavior and also leads to strange attractor. Multi-step ahead predictions have been carried out and the proposed neural network models have been optimized.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 172 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural network, which is smaller, faster and with a better generalization performance. This book is my effort to mainly showcase the capability of time series prediction using neural network approach to predict complex Nonlinear datasets for forecasting. Experiments were carried out on Netflow series. It is observed that these problems exhibit a rich chaotic behavior and also leads to strange attractor. Multi-step ahead predictions have been carried out and the proposed neural network models have been optimized.