Title :
Development of a Hopfield network for solving integral equations
Author :
Elshafiey, I. ; Udpa, L. ; Udpa, S.S.
Author_Institution :
Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA
Abstract :
The authors present a novel strategy for solving integral equations using a Hopfield type network. The major advantage of this strategy is the guaranteed convergence to the globally optimum solution ensured by the causality property of the network and the continuous nature of the feedback to each node. The algorithm consists of deriving the two function minimization equations, one for the energy function of the network and the other for the least squares solution of the discretized integral equation with appropriate regularization conditions. By comparing similar terms of the two equations the circuit parameters of the network are estimated. The network is then simulated for obtaining the solution of the integral equation. Initial simulation results are presented
Keywords :
convergence of numerical methods; integral equations; least squares approximations; mathematics computing; minimisation; neural nets; Hopfield network; causality property; circuit parameters; convergence; discretized integral equation; energy function; feedback; function minimization equations; globally optimum solution; least squares solution; node; regularization conditions; simulation; Circuit simulation; Cost function; Frequency domain analysis; Integral equations; Inverse problems; Least squares approximation; Least squares methods; Minimization methods; Neural networks; Noise measurement;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155196