Abstract

By using the semi-discretization technique of differential equations, the discrete analogue of a kind of cellular neural networks with stochastic perturbations and fuzzy operations is formulated, which gives a more accurate characterization for continuous-time models than that by Euler scheme. Firstly, the existence of at least one p-th mean almost periodic sequence solution of the semi-discrete stochastic models with almost periodic coefficients is investigated by using Minkowski inequality, Hölder inequality and Krasnoselskii’s fixed point theorem. Secondly, the p-th moment global exponential stability of the semi-discrete stochastic models is also studied by using some analytical skills and the proof of contradiction. Finally, a problem of stochastic stabilization for discrete cellular neural networks is studied.

Highlights

  • Cellular neural networks (CNNs) [1] have been widely applied in psychophysics, parallel computing, perception, robotics associative memory, image processing pattern recognition and combinatorial optimization

  • There are many scholars focusing on the study of the equilibrium points, periodic solutions and global exponential stability of CNNs with time delays in literatures [2,3,4,5,6,7]

  • The main contributions of this paper are summed up as: (1) The semi-discrete analogue is established for stochastic fuzzy CNNs (2); (2) A Volterra additive equation is derived for the solution of the semi-discrete stochastic fuzzy CNNs; (3) The existence of p-th mean almost periodic sequence solutions is obtained; (4) A decision theorem is acquired for the p-th moment global exponential stability; (5) A problem of stochastic stabilization for discrete CNNs is proposed and researched

Read more

Summary

Introduction

Cellular neural networks (CNNs) [1] have been widely applied in psychophysics, parallel computing, perception, robotics associative memory, image processing pattern recognition and combinatorial optimization. Kong and Fang [50] in 2018 investigated a class of semi-discrete neutral-type neural networks with delays and some results are acquired for the existence of a unique pseudo almost periodic sequence solution which is globally attractive and globally exponentially stable. By using the semi-discretization technique [47], Krasnoselskii’s fixed point theorem and stochastic theory, the main aim of this paper is to establish some decision theorems for the existence of p-th mean almost periodic sequence solutions and p-th moment global exponential stability for the semi-discrete analogue of uncertain system (2). The main contributions of this paper are summed up as: (1) The semi-discrete analogue is established for stochastic fuzzy CNNs (2); (2) A Volterra additive equation is derived for the solution of the semi-discrete stochastic fuzzy CNNs; (3) The existence of p-th mean almost periodic sequence solutions is obtained; (4) A decision theorem is acquired for the p-th moment global exponential stability; (5) A problem of stochastic stabilization for discrete CNNs is proposed and researched. Integrating the above equation from k to t and letting t ! k + 1, we achieve the discrete analogue of system (2) as follows: xiðk þ 1Þ 1⁄4 eÀ aiðkÞxiðkÞ "

À eÀ aiðkÞ Xn
À e0:3 pfifif
Findings
Conclusions and future works

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.