Supervised learning in nongaussian pattern recognition
Periagaram K. Rajasekaran, Mandyam D. Srinath · 1971
This paper considers supervised learning, structure and parameter adaptive binary pattern recognition when a nongaussian pattern is observed in gaussian noise. To facilitate a feasible solution, certain judicious approximations are made use of. Two examples are presented to demonstrate the learning capability of the proposed algorithms.