Existence and exponential stability of almost periodic solution for neutral delay BAM neural networks with time-varying delays in leakage terms

2013 ◽  
Vol 350 (9) ◽  
pp. 2808-2825 ◽  
Author(s):  
Yongkun Li ◽  
Youqin Li
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Exponential Stability ◽  
Almost Periodic Solution ◽  
Time Varying ◽  
Bam Neural Networks ◽  
Almost Periodic ◽  
Neutral Delay

scholarly journals Almost Periodic Solution for Memristive Neural Networks with Time-Varying Delays

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Huaiqin Wu ◽  
Luying Zhang
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Exponential Stability ◽  
Global Exponential Stability ◽  
Almost Periodic Solution ◽  
Time Varying ◽  
Almost Periodic ◽  
Memristive Neural Networks ◽  
The Stability ◽  
Stability Issues

This paper is concerned with the dynamical stability analysis for almost periodic solution of memristive neural networks with time-varying delays. Under the framework of Filippov solutions, by applying the inequality analysis techniques, the existence and asymptotically almost periodic behavior of solutions are discussed. Based on the differential inclusions theory and Lyapunov functional approach, the stability issues of almost periodic solution are investigated, and a sufficient condition for the existence, uniqueness, and global exponential stability of the almost periodic solution is established. Moreover, as a special case, the condition which ensures the global exponential stability of a unique periodic solution is also presented for the considered memristive neural networks. Two examples are given to illustrate the validity of the theoretical results.

scholarly journals Stability of Almost Periodic Solution for a General Class of Discontinuous Neural Networks with Mixed Time-Varying Delays

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Yingwei Li
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Exponential Stability ◽  
Global Exponential Stability ◽  
Sufficient Conditions ◽  
Almost Periodic Solution ◽  
Linear Matrix ◽  
Time Varying ◽  
Almost Periodic ◽  
The Neural Networks

The global exponential stability issues are considered for almost periodic solution of the neural networks with mixed time-varying delays and discontinuous neuron activations. Some sufficient conditions for the existence, uniqueness, and global exponential stability of almost periodic solution are achieved in terms of certain linear matrix inequalities (LMIs), by applying differential inclusions theory, matrix inequality analysis technique, and generalized Lyapunov functional approach. In addition, the existence and asymptotically almost periodic behavior of the solution of the neural networks are also investigated under the framework of the solution in the sense of Filippov. Two simulation examples are given to illustrate the validity of the theoretical results.

scholarly journals Dynamics of Almost Periodic BAM Neural Networks with Neutral Delays

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Yaqin Li
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Lyapunov Functional ◽  
Global Exponential Stability ◽  
Neutral Type ◽  
Sufficient Conditions ◽  
Almost Periodic Solution ◽  
Time Varying ◽  
Bam Neural Networks ◽  
Almost Periodic

The paper investigates the almost periodic oscillatory properties of neutral-type BAM neural networks with time-varying delays. By employing the contracting mapping principle and constructing suitable Lyapunov functional, several sufficient conditions are established for the existence, uniqueness, and global exponential stability of almost periodic solution of the system. The results of this paper are new and a simple example is given to illustrate the effectiveness of the new results.

scholarly journals Global Stability of Almost Periodic Solution of a Class of Neutral-Type BAM Neural Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-18
Author(s):  
Tetie Pan ◽  
Bao Shi ◽  
Jian Yuan
Keyword(s):  
Neural Networks ◽  
Periodic Solution ◽  
Neutral Type ◽  
Sufficient Conditions ◽  
Variable Coefficients ◽  
Almost Periodic Solution ◽  
Bam Neural Networks ◽  
Almost Periodic ◽  
Globally Exponential Stability ◽  
First Time

A class of BAM neural networks with variable coefficients and neutral delays are investigated. By employing fixed-point theorem, the exponential dichotomy, and differential inequality techniques, we obtain some sufficient conditions to insure the existence and globally exponential stability of almost periodic solution. This is the first time to investigate the almost periodic solution of the BAM neutral neural network and the results of this paper are new, and they extend previously known results.

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