title: Robust stability analysis of interval fuzzy Cohen-Grossberg neural networks with piecewise constant argument of generalized type.
abstract: In this paper, existence and uniqueness of the solution of interval fuzzy Cohen-Grossberg neural networks with piecewise constant argument are discussed. Based on the comparison principle, it presents new theoretical results on the global robust exponential stability of interval fuzzy Cohen-Grossberg networks with piecewise constant argument. As a special case, the corresponding results of interval fuzzy recurrent neural networks with piecewise constant argument are derived. Three examples are given for illustrating validity of the obtained results.
authors.affiliation: Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
authors.forename: Gang
authors.initials: G
authors.lastname: Bao
authors.forename: Shiping
authors.initials: S
authors.lastname: Wen
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Zeng
mesh_terms: D017143:Fuzzy Logic; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D013997:Time Factors