Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
411026 | Neurocomputing | 2006 | 5 Pages |
Abstract
This paper starting from the very first principle presents a derivation of an equation estimating of the final prediction error for a neural network under the recursive least square framework. The equation is in the form:〈〈PE〉F〉T=〈TE〉TN+d1N-d2,where d1d1 and d2d2 are some values determined by the gradient of the nonlinear mapping at the true system parameter. A cheap way of estimating such prediction error based on the information obtained via the recursive least square training method is suggested.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
John Sum, Kevin Ho,