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2017, 3(1): 25-36 Back to browse issues page
A Multi Linear Discriminant Analysis Method Using a Subtraction Criteria
M Rezghi1, Amin Rastegar
1- , rezghi@modares.ac.ir
Abstract:   (2483 Views)

Linear dimension reduction has been used in different application such as image processing and pattern recognition. All these data folds the original data to vectors and project them to an small dimensions. But in some applications such we may face with data that are not vectors such as image data. Folding the multidimensional data to vectors causes curse of dimensionality and mixed the different feature together. For solving this problem in recent years some multilinear methods have been proposed. beside vector modeling that problem becomes finding the eigenvalues of matrices, in mullinear viewpoint the problem has not such analytical meaning and should be solved by optimization techniques. In this paper by reviewing a new multi linear DATER method, propose a fast method in computation of its solution.

Keywords: dimension reduction, PCA, LDA, Multilinear, MLDA
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Type of Study: Original Manuscript | Subject: stat
Received: 2017/07/1 | Revised: 2017/12/25 | Accepted: 2017/07/1 | Published: 2017/07/1 | ePublished: 2017/07/1
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rezghi M, rastegar A. A Multi Linear Discriminant Analysis Method Using a Subtraction Criteria. Journal title 2017; 3 (1) :25-36
URL: http://mmr.khu.ac.ir/article-1-2647-en.html


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Volume 3, Issue 1 (9-2017) Back to browse issues page
پژوهش‌های ریاضی Mathematical Researches
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