M. Hallas and G. Dorffner. A comparative study on feedforward and recurrent neural networks in time series prediction using gradient descent learning. In Proc. of 14th European Meeting on Cybernetics and Systems Research, volume 2, pages 644--647, 1998. Home/Search Document Details and Download
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A Comparison Between Recurrent Neural Architectures .. - Pérez-Ortiz.. (2001) (Correct)
....the signal predicted by SRN and REPN presents a stronger nonlinear character than the actual signal and makes a cascaded con guration with a subsequent linear predictor unfeasible. The performance of PRNN, however, is improved by the linear predictor. Some works have detected serious limitations [6, 7] of RNNs when applied to nonlinear numeric prediction tasks. The ndings presented in this paper suggest similar conclusions. ACKNOWLEDGEMENTS This work has been supported by the Generalitat Valenciana through grant FPI 99 14 268, and by the Spanish Comisi on Interministerial de Ciencia y ....
M. Hallas and G. Dor ner, \A comparative study on feedforward and recurrent neural networks in time series prediction using gradient descent learning," in Trappl, R. (ed.), Cybernetics and Systems 98, Proceedings of 14th European Meeting on Cybernetics and Systems Research, Vienna, 1998, pp. 644-647.
Constraint-Based Neural Network Learning for Time Series.. - Wah, Qian (Correct)
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M. Hallas and G. Dorffner. A comparative study on feedforward and recurrent neural networks in time series prediction using gradient descent learning. In Proc. of 14th European Meeting on Cybernetics and Systems Research, volume 2, pages 644--647, 1998.
Violation-Guided Neural-Network Learning For Constrained.. - Wah, Qian (2001) (Correct)
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M. Hallas and G. Dor#ner. A comparative study on feedforward and recurrent neural networks in time series prediction using gradient descent learning. In Proc. of 14th European Meeting on Cybernetics and Systems Research, volume 2, pages 644--647, 1998.
Violation-Guided Neural-Network Learning For Constrained.. - Wah, al. (2001) (Correct)
No context found.
M. Hallas and G. Dor#ner. A comparative study on feedforward and recurrent neural networks in time series prediction using gradient descent learning. In Proc. of 14th European Meeting on Cybernetics and Systems Research, volume 2, pages 644--647, 1998.
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