| 分布参数高阶随机时滞Hopfield神经网络的指数稳定性 |
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| 引用本文： | 赵碧蓉,戴喜生.分布参数高阶随机时滞Hopfield神经网络的指数稳定性[J].南京气象学院学报,2014,6(2):182-187. |
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| 作者姓名： | 赵碧蓉 戴喜生 |
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| 作者单位： | 广州大学 数学与信息科学学院, 广州, 510006;广西科技大学 电气与信息工程学院, 柳州, 545006 |
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| 基金项目： | 广州市属高校科技计划（08C018） |
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| 摘 要： | 利用Lyapunov稳定性理论，积分不等式和Halanay不等式，研究了具分布参数的高阶随机时滞 Hopfield神经网络的均方指数稳定性，得到了保证系统指数稳定且与扩散项相关的充分性条件，并给出了指数收敛率，同时放松了现有文献中对变时滞的要求，因而在一定程度上了改进了现有文献的结果.最后给出了数值算例验证所得结果的有效性.
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| 关 键 词： | 指数稳定 Hopfield神经网络 Halanay不等式 分布参数 变时滞 |
| 收稿时间： | 2014/2/18 0:00:00 |
Exponential stability of high-order stochastic Hopfield-type neuralnetworks with time-varying delays and distributed parameters |
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| ZHAO Birong and DAI Xisheng.Exponential stability of high-order stochastic Hopfield-type neuralnetworks with time-varying delays and distributed parameters[J].Journal of Nanjing Institute of Meteorology,2014,6(2):182-187. |
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| Authors: | ZHAO Birong and DAI Xisheng |
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| Institution: | Department of Applied Mathematics, Guangzhou University, Guangzhou 510006;School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou 545006 |
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| Abstract: | In this paper,a generalized stochastic model of high-order Hopfield-typeneural networks with time-varying delays and distributed parametersis considered.The sufficientconditions ensuring the exponential stability of the systems are developed by using Lyapunovstability theory,an integral inequality and Halanay''s inequality.The proposed conditions are diffusion-dependent due to the use of the new integral inequality.As a result,the obtained conditions may have some advantages over the those previously reported.As anillustration,an numerical example is worked out using the resultsobtained. |
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