This paper discusses an extended adaptive supply network simulation model that explicitly captures growth (in terms of change in size over time, and birth and death) based on Utte...
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Experimental data show that biological synapses behave quite differently from the symbolic synapses in common artificial neural network models. Biological synapses are dynamic, i....
We apply the symbolic analysis principle to pushdown systems. We represent (possibly in nite) sets of con gurations of such systems by means of nite-state automata. In order to re...
Due to computational bounds, most SVM-based phonotactic language recognition systems consider only low-order n-grams (up to n = 3), thus limiting the potential performance of this...