Convergence of gradient method for Elman networks
Volume: 29, Issue: 9, Pages: 1231 - 1238
Published: Sep 1, 2008
Abstract
The gradient method for training Elman networks with a finite training sample set is considered. Monotonicity of the error function in the iteration is shown. Weak and strong convergence results are proved, indicating that the gradient of the error function goes to zero and the weight sequence goes to a fixed point, respectively. A numerical example is given to support the theoretical...
Paper Details
Title
Convergence of gradient method for Elman networks
Published Date
Sep 1, 2008
Volume
29
Issue
9
Pages
1231 - 1238
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