Reliable stabilization for memristor-based recurrent neural networks with time-varying delays

Neurocomputing

Volumn 153, Issue , 2015, Pages 140-147

  Mathiyalagan, K ^a   Anbuvithya, R ^b   Sakthivel, R ^c   Park, Ju H ^a   Prakash, P ^b  

^a Yeungnam University   (South Korea)

^b PERIYAR UNIVERSITY   (India)

^c Sungkyunkwan University   (South Korea)

Author keywords

Memristive neural networks; Reliable control; Stabilization; Wirtinger's inequality

Indexed keywords

ASYMPTOTIC STABILITY; LINEAR MATRIX INEQUALITIES; LYAPUNOV FUNCTIONS; MEMRISTORS; NONLINEAR CONTROL SYSTEMS; STABILIZATION; STATE FEEDBACK; TIME DELAY; TIME VARYING CONTROL SYSTEMS; TIME VARYING NETWORKS;

GLOBAL ASYMPTOTIC STABILITY; LYAPUNOV-KRASOVSKII FUNCTIONAL (LKF); RECURRENT NEURAL NETWORK (RNNS); RELIABLE CONTROL; RELIABLE STABILIZATIONS; STATE FEEDBACK CONTROLLER; TIME VARYING- DELAYS; WIRTINGER'S INEQUALITY;

RECURRENT NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; FEEDBACK SYSTEM; LINEAR MATRIX INEQUALITY; LYAPUNOV KRASOVSKII THEORY; MATHEMATICAL PHENOMENA; MEMRISTOR; PHYSICAL PHENOMENA; RECURRENT NEURAL NETWORK; TIME VARYING DELAY;

EID: 84922239441     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.11.043     Document Type: Article

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