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Supervisor of Master's Candidates
Paper Publications
Convergence of Online gradient algorithm with Stochastic inputs for Pi-Sigma neural networks
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Indexed by:Conference Paper
Date of Publication:2007-04-01
Included Journals:Scopus、CPCI-S、EI
Page Number:564-+
Key Words:Pi-Sigma neural network; online gradient algorithm; stochastic input; convergence; monotonicity
Abstract:An online gradient method is presented and discussed for Pi-Sigma neural networks with stochastic inputs. The error function is proved to be monotone in the training process, and the gradient of the error function tends to zero if the weights sequence is uniformly bounded. Furthermore, after adding a moderate condition, the weights sequence itself is also proved to be convergent.