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时滞recurrent神经网络模型的全局渐近稳定性
Over-all Exponential Stability of Recurrent Neural Networks with Time-varying Delay
【摘要】 讨论了时滞recurrent神经网络模型的全局渐近稳定性,通过构造适当的Lyapuov函数,利用线性矩阵不等式,给出了一类常时滞recurrent神经网络的新的充分条件,所获的稳定性条件是时滞相关的,稳定性判别条件更宽松.最后通过一个实例说明方法的可行性.
【Abstract】 The over-all asymptotic stability of recurrent neural networks is discussed in this paper.A new sufficient condition for the asymptotic stability is presented.This condition is dependent on the size of delays and provides more space for stability judgment.A practical example is given to illustrate the applicability of this condition.
【关键词】 时滞recurrent神经网络;
全局渐近稳定性;
平衡点;
【Key words】 recurrent neural networks; time-varying delay; over-all exponential stability; equilibrium point;
【Key words】 recurrent neural networks; time-varying delay; over-all exponential stability; equilibrium point;
【基金】 国家自然科学基金项目(No.60374023);湖南省教育厅自然科学基金重点项目(04A012);湖南省自然科学基金资助(05JJ40093)
- 【文献出处】 中南林业科技大学学报 ,Journal of Central South University of Forestry & Technology , 编辑部邮箱 ,2007年03期
- 【分类号】TP183
- 【被引频次】2
- 【下载频次】43