Learning Machines : Foundations of Trainable Pattern-Classifying Systems

A learning machine, broadly defined, is any device whose actions are influenced by past experiences. The present work deals with the theory of a subclass of learning machines, those which can be trained to recognize patterns. Some well known examples of trainable pattern-classifying systems the PERCEPRON and MADALINE and MINOS networks.