Generalized Inverse Approach to Adaptive Multiclass Pattern Classification

Abstract—In this paper a least-square approach to multiclass pattern classification is undertaken. The generalized inverse computation is used to furnish a quick solution to the problem of fixed training samples. The use of recursive on-line computation is also recommended. Experimental results are presented to illustrate the approach. Both deterministic and statistical interpretations have been given to the approach. The pattern classifier proposed by Chaplin and Levadi [1] and the adaptive pattern classifier proposed by Patterson and Womack [2] are special cases of this approach.