Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique

IMR OpenIR

	Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique
其他题名	Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique
	Feng YiFu 1; Zhang QingLing 2; Feng DeZhi 2
	2012
发表期刊	CHINESE PHYSICS B
ISSN	1674-1056
卷号	21 期号:10
摘要	The global stability problem of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks (FHNNs) with time delays is investigated. Novel LMI-based stability criteria are obtained by using Lyapunov functional theory to guarantee the asymptotic stability of the FHNNs with less conservatism. Firstly, using both Finsler's lemma and an improved homogeneous matrix polynomial technique, and applying an affine parameter-dependent Lyapunov-Krasovskii functional, we obtain the convergent LMI-based stability criteria. Algebraic properties of the fuzzy membership functions in the unit simplex are considered in the process of stability analysis via the homogeneous matrix polynomials technique. Secondly, to further reduce the conservatism, a new right-hand-side slack variables introducing technique is also proposed in terms of LMIs, which is suitable to the homogeneous matrix polynomials setting. Finally, two illustrative examples are given to show the efficiency of the proposed approaches.
其他摘要	The global stability problem of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks (FHNNs) with time delays is investigated. Novel LMI-based stability criteria are obtained by using Lyapunov functional theory to guarantee the asymptotic stability of the FHNNs with less conservatism. Firstly, using both Finsler's lemma and an improved homogeneous matrix polynomial technique, and applying an affine parameter-dependent Lyapunov-Krasovskii functional, we obtain the convergent LMI-based stability criteria. Algebraic properties of the fuzzy membership functions in the unit simplex are considered in the process of stability analysis via the homogeneous matrix polynomials technique. Secondly, to further reduce the conservatism, a new right-hand-side slack variables introducing technique is also proposed in terms of LMIs, which is suitable to the homogeneous matrix polynomials setting. Finally, two illustrative examples are given to show the efficiency of the proposed approaches.
关键词	TIME-VARYING DELAYS EXPONENTIAL STABILITY STOCHASTIC STABILITY SYSTEMS Hopfield neural networks linear matrix inequality Takagi-Sugeno fuzzy model homogeneous polynomially technique
收录类别	CSCD
语种	英语
资助项目	[National Natural Science Foundation of China] ; [Natural Science Foundation of Jilin Province, China]
CSCD记录号	CSCD:4701580
引用统计	被引频次：1[CSCD] [CSCD记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/149934
专题	中国科学院金属研究所
作者单位	1.吉林师范大学 2.中国科学院金属研究所
推荐引用方式 GB/T 7714	Feng YiFu,Zhang QingLing,Feng DeZhi. Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique[J]. CHINESE PHYSICS B,2012,21(10).
APA	Feng YiFu,Zhang QingLing,&Feng DeZhi.(2012).Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique.CHINESE PHYSICS B,21(10).
MLA	Feng YiFu,et al."Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique".CHINESE PHYSICS B 21.10(2012).