Recurrent Neural Networks for Temporal Data Processing
Cardot, Hubert
Recurrent Neural Networks for Temporal Data Processing - IntechOpen 2011 - 1 electronic resource (114 p.)
Open Access
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.
Creative Commons
English
631 9789533076850 9789535155218
10.5772/631 doi
Artificial intelligence
Neural networks & fuzzy systems
Recurrent Neural Networks for Temporal Data Processing - IntechOpen 2011 - 1 electronic resource (114 p.)
Open Access
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.
Creative Commons
English
631 9789533076850 9789535155218
10.5772/631 doi
Artificial intelligence
Neural networks & fuzzy systems