Title :
Pattern Recognition by Piecewise Linear Discriminant Functions
Author :
Chang, Chin-Liang
Author_Institution :
Heuristics Laboratory, Division of Computer Research and Technology, National Institutes of Health, Bethesda, Md. 20014.
Abstract :
A piecewise linear function is represented in terms of a set of linear functions through the use of the maximum and minimum functions. A procedure for finding piecewise linear discriminant functions for pattern recognition is described. The procedure iteratively uses the accelerated relaxation method to find every linear function in a piecewise linear function. The procedure was implemented by a Fortran program. Experimental results with the program showed that the procedure is promising for obtaining piecewise linear discriminant functions.
Keywords :
Acceleration; Error analysis; Feature extraction; Pattern classification; Pattern recognition; Piecewise linear techniques; Relaxation methods; Accelerated relaxation method; concave functions; discriminant functions; disjunctive (conjunctive) normal forms; error rate; modes; multimodal data; pattern classification; piecewise linear discriminant functions; recognition rate;
Journal_Title :
Computers, IEEE Transactions on
DOI :
10.1109/TC.1973.5009179
