5. The method as set forth in claim 2 wherein said recognition models represented by each of said terminal arcs of said network produces at least one recognition parameter, said method further comprising the step of: ceasing to propagate a hypothesis score through an individual one of said recognition models if cumulative hypothesis scores within said individual model fall below a predetermined turn-off threshold after having exceeded it.
2. A method for operating a processing system to perform handwriting recognition, said method comprising the steps of: receiving an input data signal representative of a handwriting sample including at least one symbol; preprocessing said data points of said data set and generating a set of resampled data points, said resampled data points being substantially equidistantly spaced along said handwriting sample; computing a sequence of features from said resampled data points; comparing each feature to stochastic recognition models to obtain feature scores, said stochastic recognition models comprising a plurality of probability distributions; and propagating said feature scores in sequence through an evolutional grammar network for obtaining cumulative hypothesis scores using a stochastic recognition algorithm, wherein said evolutional grammar network is represented by a grammar network comprised of arcs interconnecting nodes, ones of said arcs being terminal arcs representative of respective stochastic recognition models and others of said arcs being non-terminal arcs representing respective grammar sub-networks, said nodes including a source node and a destination node to said node source such that each sequence of arcs through the network from said source node comprises a word in a predetermined vocabulary, said method further comprising the steps of: defining a first transition network having at least one non-terminal arc; recursively replacing a first non-terminal arc with transition networks, in response to the appearance of a hypothesis score meeting a predetermined turn-on criterion at said source node of a non-terminal arc, until all of said arcs emanating from said source node are terminal arcs; and generating in a memory location said recognition models represented by all of said arcs emanating from said source node.