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2015 | OriginalPaper | Chapter

A Novel Condition for Robust Stability of Delayed Neural Networks

Authors : Neyir Ozcan, Eylem Yucel, Sabri Arik

Published in: Neural Information Processing

Publisher: Springer International Publishing

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Abstract

This paper presents a novel sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of delayed neural networks by using the Homomorphic mapping and the Lyapunov stability theorems. An important feature of the obtained result is its low computational complexity as the reported result can be verified by checking some well-known properties of some certain classes of matrices, which simplify the verification of the derived result.

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previous chapter Statistical Modelling of Artificial Neural Network for Sorting Temporally Synchronous Spikes
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Literature
1.
Bao, G., Wen, S., Zeng, Z.: Robust stability analysis of interval fuzzy Cohen-Grossberg neural networks with piecewise constant argument of generalized type. Neural Netw. 33, 32–41 (2012)CrossRefMATH
2.
Deng, F., Hua, M., Liu, X., Peng, Y., Fei, J.: Robust delay-dependent exponential stability for uncertain stochastic neural networks with mixed delays. Neurocomputing 74(10), 1503–1509 (2011)CrossRef
3.
Arik, S.: An improved robust stability result for uncertain neural networks with multiple time delays. Neural Netw. 54, 1–10 (2014)CrossRefMATH
4.
Faydasicok, O., Arik, S.: A new upper bound for the norm of interval matrices with application to robust stability analysis of delayed neural networks. Neural Netw. 44, 64–71 (2013)CrossRefMATH
5.
Guo, Z., Huang, L.: LMI conditions for global robust stability of delayed neural networks with discontinuous neuron activations. Appl. Math. Comput. 215(3), 889–900 (2009)MathSciNetCrossRefMATH
6.
7.
Kao, Y.K., Guo, J.F., Wang, C.H., Sun, X.Q.: Delay-dependent robust exponential stability of Markovian jumping reaction-diffusion Cohen-Grossberg neural networks with mixed delays. J. Franklin Inst. 349(6), 1972–1988 (2012)MathSciNetCrossRefMATH
8.
Kwon, O.M., Park, J.H.: New delay-dependent robust stability criterion for uncertain neural networks with time-varying delays. Appl. Math. Comput. 205(1), 417–427 (2008)MathSciNetCrossRefMATH
9.
Liao, X.F., Wong, K.W., Wu, Z., Chen, G.: Novel robust stability for interval-delayed Hopfield neural networks. IEEE Trans. Circuits Syst. I 48(11), 1355–1359 (2001)MathSciNetCrossRefMATH
10.
Luo, M., Zhong, S., Wang, R., Kang, W.: Robust stability analysis for discrete-time stochastic neural networks systems with time-varying delays. Appl. Math. Comput. 209(2), 305–313 (2009)MathSciNetCrossRefMATH
11.
Pan, L., Cao, J.: Robust stability for uncertain stochastic neural network with delay and impulses. Neurocomputing 94(1), 102–110 (2012)CrossRef
12.
Shen, T., Zhang, Y.: Improved global robust stability criteria for delayed neural networks. IEEE Trans. Circuits Syst. II: Express Briefs 54(8), 715–719 (2007)CrossRef
13.
Wang, Z., Liu, Y., Liu, X., Shi, Y.: Robust state estimation for discrete-time stochastic neural networks with probabilistic measurement delays. Neurocomputing 74(1–3), 256–264 (2010)CrossRef
14.
Wang, Z., Zhang, H., Yu, W.: Robust exponential stability analysis of neural networks with multiple time delays. Neurocomputing 70(1315), 2534–2543 (2007)CrossRef
15.
Yang, R., Gao, H., Shi, P.: Novel robust stability criteria for stochastic Hopfield neural networks with time delays. IEEE Trans. Syst. Man Cybern. Part B: Cybern. 39(2), 467–474 (2009)CrossRef
16.
Zhang, H., Wang, Z., Liu, D.: Robust stability analysis for interval Cohen-Grossberg neural networks with unknown time-varying delays. IEEE Trans. Neural Netw. 19(11), 1942–1955 (2008)CrossRef
17.
Zhang, Z., Zhou, D.: Global robust exponential stability for second-order Cohen-Grossberg neural networks with multiple delays. Neurocomputing 73(13), 213–218 (2009)CrossRef
18.
Zheng, M., Fei, M., Li, Y.: Improved stability criteria for uncertain delayed neural networks. Neurocomputing 98(3), 34–39 (2012)CrossRef
19.
Zhu, S., Shen, Y.: Robustness analysis for connection weight matrices of global exponential stability of stochastic recurrent neural networks. Neural Netw. 38, 17–22 (2013)CrossRefMATH
Metadata
Title
A Novel Condition for Robust Stability of Delayed Neural Networks
Authors
Neyir Ozcan
Eylem Yucel
Sabri Arik
Copyright Year
2015
Book
Neural Information Processing

Print ISBN: 978-3-319-26554-4

Electronic ISBN: 978-3-319-26555-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-26555-1_31

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