Comparative Study on Fast Learning Algorithms of BP Networks
A comparative study on some typical faster learning algorithms ofBP networks is proposed. Firstly, the advantages and disadvantages of two main categories, the fast algorithms based on standard steepest descent and standard numerical optimization, are analysed by means of their work principles. Then the comparative study on convergence times and error performance of training of those faster algorithms is done by two numerical examples. The study can be used for the reference in selecting learning algorithms and developing high performance algorithms.
NETL
NSTL
万方数据
维普
