Exponential Convergence for HCNNs with Oscillating Coefficients in Leakage Terms

被引:13
作者
Jiang, Ani [1 ]
机构
[1] Hunan Univ Arts & Sci, Coll Math & Computat Sci, Changde 415000, Hunan, Peoples R China
关键词
High-order cellular neural network; Exponential convergence; Oscillating coefficient; Leakage term; HOPFIELD NEURAL-NETWORKS; TIME-VARYING DELAYS; ANTIPERIODIC SOLUTIONS; STABILITY; HRNNS; BAM;
D O I
10.1007/s11063-015-9418-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The paper is concerned with the exponential convergence for a class of high-order cellular neural networks with oscillating coefficients in leakage terms. By employing the differential inequality techniques, we establish a novel result to ensure that all solutions of the addressed system converge exponentially to zero vector. Our approach handles particular cases which were not considered in some early relevant results. An example along with its numerical simulation is presented to demonstrate the validity of the proposed result.
引用
收藏
页码:285 / 294
页数:10
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