Combined convex technique on delay-dependent stability for delayed neural networks

IEEE Transactions on Neural Networks and Learning Systems

Volumn 24, Issue 9, 2013, Pages 1459-1466

  Li, Tao ^a,b   Wang, Ting ^c   Song, Aiguo ^c   Fei, Shumin ^c  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b Zhangjiagang Research Institute of Smart Grid   (China)

^c SOUTHEAST UNIVERSITY   (China)

Author keywords

Combined convex technique; delayed neural networks (DNNs); global stability; linear matrix inequality; time varying delay

Indexed keywords

COMBINED CONVEX TECHNIQUE; DELAY-DEPENDENT STABILITY; DELAYED NEURAL NETWORKS; GLOBAL STABILITY; GLOBALLY ASYMPTOTICALLY STABLE; LYAPUNOV-KRASOVSKII FUNCTIONAL (LKF); TIME-VARYING DELAY;

LYAPUNOV FUNCTIONS; NEURAL NETWORKS; STABILITY CRITERIA;

LINEAR MATRIX INEQUALITIES;

ALGORITHM; ANIMAL; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; COMPUTER SIMULATION; HUMAN; NERVE CELL; NERVE CELL NETWORK; PHYSIOLOGY; TIME;

ALGORITHMS; ANIMALS; COMPUTER SIMULATION; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; NEURAL NETWORKS (COMPUTER); NEURONS; TIME FACTORS;

EID: 84882845831     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2013.2256796     Document Type: Article

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