An eliminating highest error (EHE) criterion in Hopfield neural networks for bilevel image restoration

Abstract A new update criterion, which is called eliminating highest error (EHE) criterion, is presented in the paper. The Hopfield neural network taking the threshold function as the neuron's output function is essentially unstable when it is working for a least squares (LS) solution in bilevel image restoration. Under the EHE criterion the network can overcome the instability and converge to a solution extremely close to the LS one. Simulation results compared with those of the ordinary Hopfield network and the simulated annealing method are presented.