A simplification of the backpropagation-through-time algorithm for optimal neurocontrol

Backpropagation-through-time (BPTT) is the temporal extension of backpropagation which allows a multilayer neural network to approximate an optimal state-feedback control law provided some prior knowledge (Jacobian matrices) of the process is available. In this paper, a simplified version of the BPT...

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Veröffentlicht in:	IEEE transactions on neural networks Jg. 8; H. 2; S. 437 - 441
Hauptverfasser:	Bersini, H., Gorrini, V.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.03.1997 Institute of Electrical and Electronics Engineers
Schlagworte:	Applied sciences Artificial intelligence Backpropagation algorithms Bioreactors Calculus Computer science; control theory; systems Connectionism. Neural networks Dynamic programming Equations Exact sciences and technology Jacobian matrices Lagrangian functions Multi-layer neural network Neural networks Optimal control State feedback Backpropagation algorithm Experimental result Optimal control Dynamic programming Neural network Optimization Multilayer network
ISSN:	1045-9227, 1941-0093
Online-Zugang:	Volltext
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