کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
388030 | 660915 | 2009 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Robust stability of uncertain fuzzy Cohen–Grossberg BAM neural networks with time-varying delays
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Robust stability of uncertain fuzzy Cohen–Grossberg BAM neural networks with time-varying delays Robust stability of uncertain fuzzy Cohen–Grossberg BAM neural networks with time-varying delays](/preview/png/388030.png)
چکیده انگلیسی
In this paper, the Takagi–Sugeno (TS) fuzzy model representation is extended to the stability analysis for uncertain Cohen–Grossberg type bidirectional associative memory (BAM) neural networks with time-varying delays using linear matrix inequality (LMI) theory. A novel LMI-based stability criterion is obtained by using LMI optimization algorithms to guarantee the asymptotic stability of uncertain Cohen–Grossberg BAM neural networks with time varying delays which are represented by TS fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 7, September 2009, Pages 10583–10588
Journal: Expert Systems with Applications - Volume 36, Issue 7, September 2009, Pages 10583–10588
نویسندگان
M. Syed Ali, P. Balasubramaniam,