Title :
High-order absolutely stable neural networks
Author :
Dembo, Amir ; Farotimi, Oluseyi ; Kailath, Thomas
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., CA, USA
fDate :
1/1/1991 12:00:00 AM
Abstract :
The stability properties of arbitrary order continuous-time dynamic neural networks are studied in the spirit of an earlier analysis of a first-order system by M.A. Cohen and S. Grossberg (1983). The corresponding class of Lyapunov function is presented and the equilibrium points are characterized. The relationships with other continuous-time models are pointed out
Keywords :
Lyapunov methods; convergence; neural nets; polynomials; stability; Lyapunov function; arbitrary order; continuous-time; dynamic networks; equilibrium points; high order type; neural networks; stability properties; Associative memory; Circuit stability; Circuits and systems; Linear programming; Lyapunov method; Neural networks; Neurons; Pattern recognition; Stability analysis; State estimation;
Journal_Title :
Circuits and Systems, IEEE Transactions on
