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.
对大型稀疏的非Hermite正定线性代数方程组,运用正规和反Hermite分裂(normal and skew-Hermitian splitting,NSS)迭代技巧,提出了一种两参数预处理NSS迭代法,它实际上是预处理NSS方法的推广.理论分析表明,新方法收敛于线性方程组的唯一解.进一步地,推导了出现于新方法中的两个参数的最优选取,计算了对应的迭代谱的上界的最小值.新方法的实际实施中,还将不完全LU分解和增量未知元选做了两类预处理子.数值结果对所给方法的收敛性理论和有效性予以了证实.
