Global exponential stability and existence of periodic solution of Hopfield-type neural networks with impulses

Physics Letters, Section A: General, Atomic and Solid State Physics

Volumn 333, Issue 1-2, 2004, Pages 62-71

  Li, Yongkun ^a   Lu, Linghong ^a  

^a YUNNAN UNIVERSITY   (China)

Author keywords

Coincidence degree theory; Global stability; Impulsive equations; Neural networks; Periodic solution

Indexed keywords

LYAPUNOV FUNCTIONS; NEURAL NETWORKS;

COINCIDENCE DEGREE THEORY; CONTINUATION THEOREM OF COINCIDENCE DEGREE THEORY; GLOBAL EXPONENTIAL STABILITY; GLOBAL STABILITY; HOPFIELD TYPE NEURAL NETWORKS; IMPULSIVE EQUATIONS; PERIODIC SOLUTION; POSITIVE INTEGERS;

HOPFIELD NEURAL NETWORKS;

ANALYTIC METHOD; ARTICLE; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; NERVE CELL NETWORK; QUANTUM THEORY;

EID: 8444222334     PISSN: 03759601     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.physleta.2004.09.083     Document Type: Article

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