Title :
Supervised learning in nongaussian pattern recognition
Author :
Rajasekaran, P. ; Srinath, M.
Author_Institution :
SMU Institute of Technology, Dallas, Texas
Abstract :
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.
Keywords :
Pattern recognition; Supervised learning;
Conference_Titel :
Decision and Control, 1971 IEEE Conference on
Conference_Location :
Miami Beach, FL, USA
DOI :
10.1109/CDC.1971.271010
