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math_math
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shj2006: ½ð±Ò+10, ¡ï¡ï¡ï¡ï¡ï×î¼Ñ´ð°¸ 2014-03-29 15:56:19
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ÒѾ¼ìË÷ÁË, ¼ûÏÂÃæÏêϸ¼ìË÷±¨¸æ Finite-Time Boundedness for a Class of Delayed Markovian Jumping Neural Networks with Partly Unknown Transition Probabilities ×÷Õß:Liang, L (Liang, Li) ABSTRACT AND APPLIED ANALYSIS ÎÄÏ׺Å: 597298 DOI: 10.1155/2014/597298 ³ö°æÄê: 2014 ²é¿´ÆÚ¿¯ÐÅÏ¢ ¿ª·Å»ñȡָ±ê ÕªÒª This paper is concerned with the problem of finite-time boundedness for a class of delayed Markovian jumping neural networks with partly unknown transition probabilities. By introducing the appropriate stochastic Lyapunov-Krasovskii functional and the concept of stochastically finite-time stochastic boundedness for Markovian jumping neural networks, a new method is proposed to guarantee that the state trajectory remains in a bounded region of the state space over a prespecified finite-time interval. Finally, numerical examples are given to illustrate the effectiveness and reduced conservativeness of the proposed results. ¹Ø¼ü´Ê KeyWords Plus:EXPONENTIAL STABILITY ANALYSIS; UNCERTAIN NONLINEAR-SYSTEMS; H-INFINITY CONTROL; VARYING DELAYS; STATE ESTIMATION; STOCHASTIC-SYSTEMS; PASSIVITY ANALYSIS; DISCRETE; STABILIZATION; FEEDBACK ×÷ÕßÐÅÏ¢ ͨѶ×÷ÕßµØÖ·: Liang, L (ͨѶ×÷Õß) Hainan Univ, Coll Informat Sci & Technol, Haikou 570228, Peoples R China. µØÖ·: [ 1 ] Hainan Univ, Coll Informat Sci & Technol, Haikou 570228, Peoples R China µç×ÓÓʼþµØÖ·:liangli7841@126.com »ù½ð×ÊÖúÖÂл »ù½ð×ÊÖú»ú¹¹ ÊÚȨºÅ Natural Science Foundation of Hainan province 111002 ²é¿´»ù½ð×ÊÖúÐÅÏ¢ ³ö°æÉÌ HINDAWI PUBLISHING CORPORATION, 410 PARK AVENUE, 15TH FLOOR, #287 PMB, NEW YORK, NY 10022 USA Àà±ð / ·ÖÀà Ñо¿·½Ïò:Mathematics Web of Science Àà±ð:Mathematics, Applied; Mathematics ÎÄÏ×ÐÅÏ¢ ÎÄÏ×ÀàÐÍ:Article ÓïÖÖ:English Èë²ØºÅ: WOS:000332227700001 ISSN: 1085-3375 µç×Ó ISSN: 1687-0409 ÆÚ¿¯ÐÅÏ¢ Impact Factor (Ó°ÏìÒò×Ó): Journal Citation Reports® ÆäËûÐÅÏ¢ IDS ºÅ: AC1AX Web of Science ºËÐĺϼ¯ÖÐµÄ "ÒýÓõIJο¼ÎÄÏ×": 39 Web of Science ºËÐĺϼ¯ÖÐµÄ "±»ÒýƵ´Î": 0 |

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