DISCRIMINANT ANALYSIS IN SECURITY ASSESSMENT OF POWER SYSTEMS BY STATISTICAL PATTERN RECOGNITION

Author(s):  
G. Garcia ◽  
J. Fantin ◽  
B. Dubuisson
Biometrics ◽  
1994 ◽  
Vol 50 (1) ◽  
pp. 317
Author(s):  
C. A. Glasbey ◽  
G. McLachlan ◽  
M. Pavel

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Rina Widya Sari ◽  
Ismail Husein

Statistical pattern recognition is a system that aims to classify a number of objects to a number of categories or classes. Given a data matrix A, A = {Π1, Π2,…, Πk} where Πi consist of ni point data of ith class then patterns in each classes can classify and separate distance of within and between-class in datasets. In this paper, Symmetric Two-Dimensional Linear Discriminant Analysis proposed to maximize the between-class scatter matrices (Sb) and minimize the within-class scatter matrices (Sw), and can recognition the symmetric capital letter by hand writing such as A, B, C, D, E, H, I, K, M, O, S, U, V, W and Y by using ADL2-D algorithm.


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