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Proceedings Paper

Dynamic recurrent Elman neural network based on immune clonal selection algorithm
Author(s): Limin Wang; Xuming Han; Ming Li
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Paper Abstract

Owing to the immune clonal selection algorithm introduced into dynamic threshold strategy has better advantage on optimizing multi-parameters, therefore a novel approach that the immune clonal selection algorithm introduced into dynamic threshold strategy, is used to optimize the dynamic recursion Elman neural network is proposed in the paper. The concrete structure of the recursion neural network, the connect weight and the initial values of the contact units etc. are done by evolving training and learning automatically. Thus it could realize to construct and design for dynamic recursion Elman neural networks. It could provide a new effective approach for immune clonal selection algorithm optimizing dynamic recursion neural networks.

Paper Details

Date Published: 8 June 2012
PDF: 5 pages
Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 83342L (8 June 2012); doi: 10.1117/12.956430
Show Author Affiliations
Limin Wang, Jilin Univ. of Finance and Economics (China)
Xuming Han, Changchun Univ. of Technology (China)
Ming Li, Jilin Univ. of Finance and Economics (China)


Published in SPIE Proceedings Vol. 8334:
Fourth International Conference on Digital Image Processing (ICDIP 2012)
Mohamed Othman; Sukumar Senthilkumar; Xie Yi, Editor(s)

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