Title :
A second order recursive prediction error algorithm for diagonal recurrent neural networks
Author :
Wang, Yongji ; Fernholz, Gregor ; Engell, Sebastian
Author_Institution :
Dept. of Chem. Eng., Dortmund Univ., Germany
Abstract :
A recursive prediction error (RPE) learning algorithm with second order of convergence for diagonal recurrent neural networks (DRNN) is presented. A guideline for the choice of optimal learning rate is derived from convergence analysis based on Lyapunov theory. With application of this method to model a batch distillation column, the results show that the RPE based DRNN has higher modeling precision and requires a shorter computation time compared to backpropagation (BP) based training of multilayer perceptron nets (MLP)
Keywords :
Lyapunov methods; convergence; distillation; learning (artificial intelligence); recurrent neural nets; Lyapunov theory; batch distillation column; convergence analysis; diagonal recurrent neural networks; learning algorithm; optimal learning rate; second order recursive prediction error algorithm; Acceleration; Backpropagation; Chemical engineering; Convergence; Distillation equipment; Multilayer perceptrons; Neural networks; Neurons; Prediction algorithms; Recurrent neural networks;
Conference_Titel :
Control Applications, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Trieste
Print_ISBN :
0-7803-4104-X
DOI :
10.1109/CCA.1998.728319
