An Improved LDA method is proposed in this paper. A weakness of Existing fuzzy LDA
model is that the class mean vector in the expression of between-class scatter matrix is …

In this paper, we propose a novel method for feature extraction and recognition, namely,
complete fuzzy LDA (CFLDA). CFLDA combines the complete LDA and fuzzy set theory …

Recently, linear discriminant analysis (LDA) was proposed to manifold learning and pattern
classification. LDA, a supervised method, aims to find the optimal set of projection vectors …

Fuzzy linear discriminate analysis (FLDA), the principle of which is the remedy of class
means via fuzzy optimization, is proven to be an effective feature extraction approach for …

This paper proposes a new method of face image feature extraction, namely, the fuzzy
2DLDA (F2DLDA) based on the 2D fisher discriminant criterion and fuzzy set theory. In the …

In this paper, some studies have been made on the essence of fuzzy linear discriminant
analysis (F-LDA) algorithm and fuzzy support vector machine (FSVM) classifier, respectively …

Generalized two-dimensional Fisher's linear discriminant (G-2DFLD) is an effective feature
extraction technique that maximizes class separability along row and column directions …

Classical Linear Discriminant Analysis (LDA) is usually suffers from the small sample size
(SSS) problem when dealing with the high dimensional face data. Many methods have been …

The paper addresses the face recognition problem by modifying the Fuzzy Fisherface
classification method. In conventional methods, the relationship of each face to a class is …

Traditional Fisher linear discriminant analysis (FLDA) method is a promising algorithm for
face recognition. However, FLDA does not utilize the geometric distribution information of …