Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique
文献类型：期刊论文
| 作者 | Feng YiFu1; Zhang QingLing2; Feng DeZhi2 |
| 刊名 | CHINESE PHYSICS B
 |
| 出版日期 | 2012 |
| 卷号 | 21期号:10 |
| 关键词 | TIME-VARYING DELAYS EXPONENTIAL STABILITY STOCHASTIC STABILITY SYSTEMS Hopfield neural networks linear matrix inequality Takagi-Sugeno fuzzy model homogeneous polynomially technique |
| ISSN号 | 1674-1056 |
| 其他题名 | Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique |
| 英文摘要 | 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. |
| 资助项目 | [National Natural Science Foundation of China] ; [Natural Science Foundation of Jilin Province, China] |
| 语种 | 英语 |
| CSCD记录号 | CSCD:4701580 |
| 源URL | [http://ir.imr.ac.cn/handle/321006/149933]  |
| 专题 | 金属研究所_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). |
入库方式： OAI收割
来源：金属研究所
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