Computing Gabor expansion coefficients by TH neural network

It is proposed that the Gabor (1946) expansion coefficients of a periodic (or finite) discrete signal in both the critical sampling case and the oversampling case can be computed by TH neural networks. Theoretical analysis and simulations show that this network will certainly provide approximate solutions arbitrarily close to the accurate one within the time of the order of time constants of this network without any programming complexity.