Globalμ-Stability Analysis for Impulsive Stochastic Neural Networks with Unbounded Mixed Delays | Zendy

Lizi Yin | Zendy; Xinchun Wang | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Globalμ-Stability Analysis for Impulsive Stochastic Neural Networks with Unbounded Mixed Delays

Author(s) -

Lizi Yin,

Xinchun Wang

Publication year - 2013

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2013/746241

Subject(s) - algorithm , mathematics , artificial neural network , matlab , stability (learning theory) , machine learning , artificial intelligence , computer science , operating system

We investigate the global μ-stability in the mean square of impulsive stochastic neural networks with unbounded time-varying delays and continuous distributed delays. By choosing an appropriate Lyapunov-Krasovskii functional, a novel robust stability condition, in the form of linear matrix inequalities, is derived. These sufficient conditions can be tested by MATLAB LMI software packages. The results extend and improve the earlier publication. Two numerical examples are provided to illustrate the effectiveness of the obtained theoretical results

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research