Robust stability of delayed fuzzy Cohen-Grossberg neural networks

abstract

• In this paper, using a linear matrix inequality and a differential inequality, we obtain an exponentially robust stability criterion for interval fuzzy CohenGrossberg type neural networks with time-varying delays. The criterion can be easily applied to the design of fuzzy general neural networks. 2010 Elsevier Ltd. All rights reserved.

authors

• Huang, Tingwen

published proceedings

• COMPUTERS & MATHEMATICS WITH APPLICATIONS

author list (cited authors)

• Huang, T.

citation count

• 36

complete list of authors

• Huang, Tingwen

publication date

• April 2011

publisher

• Elsevier  Publisher

published in

• Computers and Mathematics with Applications  Journal

keywords

• Delays
• Fuzzy Cohen-grossberg Neural Networks
• Linear Matrix Inequality

Digital Object Identifier (DOI)

• 10.1016/j.camwa.2010.09.037

start page

• 2247

end page

• 2250

volume

• 61

issue

• 8

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.camwa.2010.09.037

user-defined tag

• 10 Reduced Inequalities