Fractional neural network models for nonlinear Riccati systems
Fractional neural network models for nonlinear Riccati systems
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Publisher
London: Springer London
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Language
English
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Publisher
London: Springer London
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Contents
In this article, strength of fractional neural networks (FrNNs) is exploited to find the approximate solutions of nonlinear systems based on Riccati equations of arbitrary order. The feed-forward artificial FrNN are used to develop the energy function of the system by defining an error function in mean square sense. Design parameters for optimizati...
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Full title
Fractional neural network models for nonlinear Riccati systems
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TN_cdi_proquest_journals_2203235152
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2203235152
Other Identifiers
ISSN
0941-0643
E-ISSN
1433-3058
DOI
10.1007/s00521-017-2991-y
