Existence and Exponential Stability of Equilibrium Point for Fuzzy BAM Neural Networks with Infinitely Distributed Delays and Impulses on Time Scales | Zendy

Yongkun Li | Zendy; Lijie Sun | Zendy; Yang Li | Zendy

Open Access

Existence and Exponential Stability of Equilibrium Point for Fuzzy BAM Neural Networks with Infinitely Distributed Delays and Impulses on Time Scales

Author(s) -

Yongkun Li,

Lijie Sun,

Yang Li

Publication year - 2014

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2014/721586

Subject(s) - uniqueness , equilibrium point , exponential stability , mathematics , control theory (sociology) , class (philosophy) , artificial neural network , stability (learning theory) , fuzzy logic , point (geometry) , lyapunov function , computer science , mathematical analysis , nonlinear system , differential equation , control (management) , artificial intelligence , physics , geometry , quantum mechanics , machine learning

By using the fixed point theorem and constructing a Lyapunov functional, we establish some sufficient conditions on the existence, uniqueness, and exponential stability of equilibrium point for a class of fuzzy BAM neural networks with infinitely distributed delays and impulses on time scales. We also present a numerical example to show the feasibility of obtained results. Our example also shows that the described time and continuous neural time networks have the same dynamic behaviours for the stability

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