کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6866167 | 679096 | 2015 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Hâ state estimation for discrete-time delayed neural networks with randomly occurring quantizations and missing measurements
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This paper is concerned with the Hâ state estimation problem for a class of discrete-time neural networks with time-varying delays, randomly occurring quantizations (ROQs) as well as missing measurements. The phenomena of ROQ and missing measurements are governed by a Bernoulli distributed stochastic sequence. The purpose of the addressed problem is to design a state estimator such that the dynamics of the estimation error is exponentially stable in the mean square and the prescribed Hâ performance constraint is satisfied. By constructing proper Lyapunov-Krasovskii functionals and employing stochastic analysis techniques, sufficient conditions are derived to ensure the existence of the desired estimator. Furthermore, the explicit expression of the gain of the desired estimator is described in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite programme method. Finally, a numerical example is employed to demonstrate the effectiveness and applicability of the proposed estimator design approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 148, 19 January 2015, Pages 388-396
Journal: Neurocomputing - Volume 148, 19 January 2015, Pages 388-396
نویسندگان
Jie Zhang, Zidong Wang, Derui Ding, Xiaohui Liu,