The paper presents the efficient training program of multilayer feedforward neural networks. It is based on the best second order optimization algorithms, including variable metric and conjugate gradient as well as application of directional minimization in each step. The method applies the signal flow graph approach for gradient generation. The results of standard numerical tests are given. The efficiency of the program tested on many examples, including symmetry, parity, dichotomy logistic and 2-spiral problems has shown considerable speed-up over the best, already known reported results.<>
Efficient supervised learning of multilayer feedforward neural networks
1994-01-01
336708 byte
Conference paper
Electronic Resource
English
Efficient Supervised Learning of Multilayer Feedforward Neural Networks
British Library Conference Proceedings | 1994
|An Efficient Learning Algorithm for Large-scale Feedforward Neural Networks and Its Application
British Library Online Contents | 2003
|A Homotopy Recursive Algorithm for Multilayer Feedforward Neural Network
British Library Conference Proceedings | 1994
|British Library Conference Proceedings | 1994
|