This paper proposes Fractional-order Hopfield Neural Networks (FHNN). This network is mainly based on the classic well-known Hopfield net in which fractance components with fractional order derivatives, replace capacitors. Stability of FHNN is fully investigated through energy-like function analysis. To show how effective the FHNN network is, an illustrative example for parameter estimation problem of the second-order system is finally considered in the paper. The results of simulation are very promising. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Boroomand, A., & Menhaj, M. B. (2009). Fractional-order hopfield neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5506 LNCS, pp. 883–890). https://doi.org/10.1007/978-3-642-02490-0_108
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