An adaptive Gauss-Newton algorithm for training multilayer nonlinear filters that have embedded memory (Q1971595)
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scientific article; zbMATH DE number 1422952
| Language | Label | Description | Also known as |
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| English | An adaptive Gauss-Newton algorithm for training multilayer nonlinear filters that have embedded memory |
scientific article; zbMATH DE number 1422952 |
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An adaptive Gauss-Newton algorithm for training multilayer nonlinear filters that have embedded memory (English)
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7 June 2000
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The authors consider multilayer dynamic Volterra networks. The networks consist of linear dynamic filters with nonlinear generalized single layer subnets. A modified Gauss-Newton optimization technique is used as a training algorithm. It is applied to modeling the inverse of a nonlinear dynamic tracking system.
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neural networks
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multilayer nonlinear adaptive filters
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Gauss-Newton optimization training
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inverse of a nonlinear dynamic tracking system
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