Title :
Efficient supervised learning of multilayer feedforward neural networks
Author :
Osowski, Stanislaw ; Stodolski, Maciej ; Bojarczak, Piotr
Author_Institution :
Inst. of the Theory of Electr. Measure., Tech. Univ. Warsaw, Poland
Abstract :
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
Keywords :
feedforward neural nets; interpolation; learning (artificial intelligence); numerical analysis; optimisation; search problems; 2-spiral problems; conjugate gradient; dichotomy logistic; directional minimization; multilayer feedforward neural networks; parity; second order optimization; signal flow graph approach; supervised learning; symmetry; variable metric; Feedforward neural networks; Flow graphs; Logistics; Minimization methods; Multi-layer neural network; Neural networks; Nonhomogeneous media; Signal generators; Supervised learning; Testing;
Conference_Titel :
Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on
Print_ISBN :
0-7803-1865-X
DOI :
10.1109/SIPNN.1994.344885
