Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
407189 | Neurocomputing | 2016 | 6 Pages |
Abstract
This paper investigates the problem of dissipativity analysis for discrete-time fuzzy neural network with parameter uncertainties based on interval type-2 (IT2) fuzzy model. The parameter uncertainties are handled via the lower and upper membership functions. The original sufficient conditions are presented by a set of linear matrix inequalities (LMIs) to guarantee the dissipativity of the resulting system. The main contribution of this paper is that the discrete-time form of the IT2 T–S fuzzy neural network with leakage and time-varying delays is first proposed. Finally, a numerical example is provided to testify the effectiveness of the proposed results.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Zhiqiang Ma, Guanghui Sun, Di Liu, Xing Xing,