{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T21:09:12Z","timestamp":1649020152110},"reference-count":48,"publisher":"World Scientific Pub Co Pte Lt","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Bifurcation Chaos"],"published-print":{"date-parts":[[2009,10]]},"abstract":"<jats:p> In the current paper, a class of stochastic cellular neural networks with reaction\u2013diffusion effects, both discrete and distributed time delays, is studied. Several sufficient conditions guaranteeing the almost sure and pth moment exponential stability of its equilibrium solution are respectively obtained through analytic methods such as employing Lyapunov functional, applying It\u00f4's formula, inequality techniques, embedding in Banach space, Matrix analysis and semimartingale convergence theorem. The yielded conclusions, which are independent of diffusion terms and delays, assume much less restrictions on activation functions and interconnection weights, and can be applied within a broader range of neural networks. Moreover, through the obtained results, it could be noted that noise will affect the exponential stability of the system. For illustration, two examples are given to show the feasibility of results. <\/jats:p>","DOI":"10.1142\/s0218127409024815","type":"journal-article","created":{"date-parts":[[2009,12,15]],"date-time":"2009-12-15T11:45:55Z","timestamp":1260877555000},"page":"3373-3386","source":"Crossref","is-referenced-by-count":1,"title":["EXPONENTIAL p-STABILITY OF STOCHASTIC REACTION\u2013DIFFUSION CELLULAR NEURAL NETWORKS WITH MULTIPLE DELAYS"],"prefix":"10.1142","volume":"19","author":[{"given":"RANCHAO","family":"WU","sequence":"first","affiliation":[{"name":"School of Mathematics, Anhui University, Hefei 230039, P. R. 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