DocumentCode
1133557
Title
A New Weighted Generalized Inverse Algorithm for Pattern Recognition
Author
Al-Alaoui, Mohamad Adnan
Author_Institution
Department of Electrical Engineering, Royal Scientific Society
Issue
10
fYear
1977
Firstpage
1009
Lastpage
1017
Abstract
A new weighted mean-square-error (MSE) procedure for pattern classification is introduced. The method iteratively repeats the misclassified samples. Three theorems on redundancy and the least square generalized inverse solution for an inconsistent set of equations are presented and proved. The resulting algorithm is presented together with a convergence proof for the linearly separable case. Several examples are included that demonstrate the advantage of the method over the MSE solution for both the separable and nonseparable cases.
Keywords
Algorithm, design set, discriminant function, generalized inverse, mean-square error, pattern classification, redundancy, weight vector.; Cost function; Equations; Iterative algorithms; Least squares approximation; Least squares methods; Pattern classification; Pattern recognition; Redundancy; Relaxation methods; Vectors; Algorithm, design set, discriminant function, generalized inverse, mean-square error, pattern classification, redundancy, weight vector.;
fLanguage
English
Journal_Title
Computers, IEEE Transactions on
Publisher
ieee
ISSN
0018-9340
Type
jour
DOI
10.1109/TC.1977.1674736
Filename
1674736
Link To Document