Downloads & Free Reading Options - Results

During the last two decades, statistical pattern recognition was well developed in theory and applications with the peak activity in the late sixties. The paper outlines important but unsolved problem areas in statistical pattern recognition and then takes a new and close look at some problems which are related to the finite sample size constraint. In an effort to bridge the gap between theory and practice, constructive solutions are provided for the problems: finite sample distance and information measures, finite sample nearest neighbor decision rule, contextual analysis, decision rules based on discrete and continuous measurements, and finite sample stochastic syntax analysis. It is concluded that there are still many challenging problems to be solved in statistical pattern recognition and every effort should be made such that the theory works well in practice.