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State Estimation for Discrete-Time Fuzzy Cellular Neural Networks with Mixed Time Delays
- Source :
- Mathematical Problems in Engineering, Vol 2014 (2014)
- Publication Year :
- 2014
- Publisher :
- Hindawi Limited, 2014.
-
Abstract
- This paper is concerned with the exponential state estimation problem for a class of discrete-time fuzzy cellular neural networks with mixed time delays. The main purpose is to estimate the neuron states through available output measurements such that the dynamics of the estimation error is globally exponentially stable. By constructing a novel Lyapunov-Krasovskii functional which contains a triple summation term, some sufficient conditions are derived to guarantee the existence of the state estimator. The linear matrix inequality approach is employed for the first time to deal with the fuzzy cellular neural networks in the discrete-time case. Compared with the present conditions in the form ofM-matrix, the results obtained in this paper are less conservative and can be checked readily by the MATLAB toolbox. Finally, some numerical examples are given to demonstrate the effectiveness of the proposed results.
- Subjects :
- Class (set theory)
Article Subject
General Mathematics
lcsh:Mathematics
General Engineering
Linear matrix inequality
State (functional analysis)
lcsh:QA1-939
Computer Science::Digital Libraries
Exponential function
Term (time)
Matrix (mathematics)
Discrete time and continuous time
Exponential stability
Control theory
lcsh:TA1-2040
Computer Science::Mathematical Software
lcsh:Engineering (General). Civil engineering (General)
Mathematics
Subjects
Details
- Language :
- English
- ISSN :
- 15635147
- Volume :
- 2014
- Database :
- OpenAIRE
- Journal :
- Mathematical Problems in Engineering
- Accession number :
- edsair.doi.dedup.....fd76e99c3cf68977d467e368dd36a900