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Synopsis
The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems.
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Recurrent Neural Networks for Temporal Data Processing
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Recurrent Neural Networks for Temporal Data Processing
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Recurrent Neural Networks for Temporal Data Processing
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems. 114 pp. Englisch. Seller Inventory # 9789533076850
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Recurrent Neural Networks for Temporal Data Processing
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Recurrent Neural Networks for Temporal Data Processing
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems. Seller Inventory # 9789533076850
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Recurrent Neural Networks for Temporal Data Processing
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Buch. Condition: Neu. Neuware -The RNNs (Recurrent Neural Networks) are a general case of artificial neural networks where the connections are not feed-forward ones only. In RNNs, connections between units form directed cycles, providing an implicit internal memory. Those RNNs are adapted to problems dealing with signals evolving through time. Their internal memory gives them the ability to naturally take time into account. Valuable approximation results have been obtained for dynamical systems.Books on Demand GmbH, Überseering 33, 22297 Hamburg 114 pp. Englisch. Seller Inventory # 9789533076850
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Recurrent Neural Networks for Temporal Data Processing
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