Global Stability of Clifford-Valued Recurrent Neural Networks With Mixed Time-Varying Delays

SHU Han-qi; SONG Qian-kun

doi:10.21656/1000-0887.370319

Volume 38 Issue 5

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SHU Han-qi, SONG Qian-kun. Global Stability of Clifford-Valued Recurrent Neural Networks With Mixed Time-Varying Delays[J]. Applied Mathematics and Mechanics, 2017, 38(5): 513-525. doi: 10.21656/1000-0887.370319

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Global Stability of Clifford-Valued Recurrent Neural Networks With Mixed Time-Varying Delays

doi: 10.21656/1000-0887.370319

SHU Han-qi¹,
SONG Qian-kun²

¹School of Economics and Management, Chongqing Jiaotong University, Chongqing 400074, P.R.China;²Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, P.R.China

Funds: The National Natural Science Foundation of China(61273021; 61473332)

Received Date: 2016-10-17
Rev Recd Date: 2017-03-23
Publish Date: 2017-05-15

Abstract

Abstract

The global exponential stability of Clifford-valued recurrent neural networks (RNNs) with both asynchronous time-varying and continuously distributed delays was studied. First, the existence and uniqueness of the equilibrium points of delayed Clifford-valued RNNs were proved with the inequality technique and the M-matrix properties. Then, based on the mathematical analysis method, some determinant conditions ensuring the global exponential stability of such systems were obtained. The simulation results of a numerical example substantiate the effectiveness of the theoretical analysis.
- Clifford-valued recurrent neural network,
- equilibrium point,
- asynchronous time-varying delay,
- distributed delay,
- global exponential stability,
- M-matrix

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References

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