Title :
Convergence analysis of stochastic pseudo-gradient algorithms and application to learning in feedforward neural networks
Author :
V. Tadic;S. Stankovic
Author_Institution :
Autom. Control Lab., Mihajlo Pupin Inst., Belgrade, Serbia
Abstract :
The convergence of a class of stochastic pseudo-gradient algorithms driven by correlated data sequences is considered in this paper. The obtained results are applied to a learning algorithm for feedforward neural networks and sufficient conditions for its convergence are determined.
Keywords :
"Convergence","Algorithm design and analysis","Stochastic processes","Neural networks","Feedforward neural networks","Random variables","Multilayer perceptrons","Intelligent networks","Automatic control","Laboratories"
Conference_Titel :
Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
Print_ISBN :
0-7803-3956-8
DOI :
10.1109/ISIT.1997.613123
