Convergence and Stability of the Split-Step θ-Milstein Method for Stochastic Delay Hopfield Neural Networks
Joint Authors
Xie, Wenwen
Mitsui, Taketomo
Guo, Qian
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-07
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
A new splitting method designed for the numerical solutions of stochastic delay Hopfield neural networks is introduced and analysed.
Under Lipschitz and linear growth conditions, this split-step θ-Milstein method is proved to have a strong convergence of order 1 in mean-square sense, which is higher than that of existing split-step θ-method.
Further, mean-square stability of the proposed method is investigated.
Numerical experiments and comparisons with existing methods illustrate the computational efficiency of our method.
American Psychological Association (APA)
Guo, Qian& Xie, Wenwen& Mitsui, Taketomo. 2013. Convergence and Stability of the Split-Step θ-Milstein Method for Stochastic Delay Hopfield Neural Networks. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-451392
Modern Language Association (MLA)
Guo, Qian…[et al.]. Convergence and Stability of the Split-Step θ-Milstein Method for Stochastic Delay Hopfield Neural Networks. Abstract and Applied Analysis No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-451392
American Medical Association (AMA)
Guo, Qian& Xie, Wenwen& Mitsui, Taketomo. Convergence and Stability of the Split-Step θ-Milstein Method for Stochastic Delay Hopfield Neural Networks. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-451392
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-451392