An Experimental Investigation of a Class of Pattern Recognition Synthesis Algorithms

This paper discusses a class of pattern-recognition decision-making procedures which can be efficiently mechanized by a network of linear threshold devices. A theoretical discussion of four decision techniques (which are members of the above-mentione class) is augmented by an experimental program which investigates questions not amenable to analysis.