Title :
EBP-learning algorithm for multi-layered and inter-connected neural networks
Author :
Yamamoto, Yoshihiro
Author_Institution :
Fac. of Eng., Tottori Univ., Japan
Abstract :
The EBP algorithm has been proposed by the author for a multi-layered neural network without using a gradient method. This algorithm consists of two steps. First, fictitious teacher signals for the outputs of each hidden layer unit are algebraically determined by an error backpropagation (EBP) method. Then, the weight parameters are determined by using an orthogonal projection (EBP-OP) method, or an exponentially weighted least squares (EBP-EWLS) method. It is shown that the algorithm is also applicable for an inter-connected neural network
Keywords :
backpropagation; multilayer perceptrons; error backpropagation; exponentially weighted least squares method; fictitious teacher signals; inter-connected neural networks; multi-layered neural networks; orthogonal projection; Computer networks; Control systems; Electronic mail; Gradient methods; Knowledge engineering; Least squares methods; Multi-layer neural network; Neural networks; Pattern recognition; Supervised learning;
Conference_Titel :
SICE '98. Proceedings of the 37th SICE Annual Conference. International Session Papers
Conference_Location :
Chiba
DOI :
10.1109/SICE.1998.742918
