Convergence Properties of a Modified Temporal Anti-Hebbian Model
This paper proposes a modification to Girolami and Fyfe’s temporal variant of Foldiak’s first model. In the original temporal model asymmetric memory based lateral weights are adapted using a cross-correlation criterion and compared with information maximisation applied to the blind separation of sources which have experienced convolved mixing. In our new model the weights are adapted using a linearised discontinuous function which shares the same quadrature sign behaviour as the decorrelation function. The model provides separation and restoration of convolved mixes of signals where network weights converge very closely to ideal FIR deconvolving filter coefficients. We compare the convergence properties of a ‘linearised correlation’ model with that of the original model and examine potential for improvement of convergence behaviour.