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Soft Computing

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01.05.2013 | Methodologies and Application

Dynamic characteristic of a multiple chaotic neural network and its application

verfasst von: Gang Yang, Junyan Yi

Erschienen in: Soft Computing | Ausgabe 5/2013

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Abstract

Based on chaotic neural network, a multiple chaotic neural network algorithm combining two different chaotic dynamics sources in each neuron is proposed. With the effect of self-feedback connection and non-linear delay connection weight, the new algorithm can contain more powerful chaotic dynamics to search the solution domain globally in the beginning searching period. By analyzing the dynamic characteristic and the influence of cooling schedule in simulated annealing, a flexible parameter tuning strategy being able to promote chaotic dynamics convergence quickly is introduced into our algorithm. We show the effectiveness of the new algorithm in two difficult combinatorial optimization problems, i.e., a traveling salesman problem and a maximum clique problem.

Vorheriger Artikel Robust H ∞ output feedback control with pole placement constraints for uncertain discrete-time fuzzy systems

Nächster Artikel Large data sets classification using convex–concave hull and support vector machine

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Titel: Dynamic characteristic of a multiple chaotic neural network and its application
verfasst von: Gang Yang
Junyan Yi
Publikationsdatum: 01.05.2013
Verlag: Springer-Verlag
Erschienen in: Soft Computing / Ausgabe 5/2013
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-012-0948-8

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