Transformation Technique for Null Space-Based Linear Discriminant Analysis with Lagrange Method 


Vol. 38,  No. 2, pp. 208-212, Feb.  2013


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  Abstract

Due to the singularity of the within-class scatter, linear discriminant analysis (LDA) becomes ill-posed for small sample size (SSS) problems. An extension of LDA, the null space-based LDA (NLDA) provides good discriminant performances for SSS problems. In this paper, by applying the Lagrange technique, the procedure of transforming the problem of finding the feature extractor of NLDA into a linear equation problem is derived.

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  Cite this article

[IEEE Style]

Y. Hou, H. Min, I. Song, M. S. Choi, S. Park, S. R. Lee, "Transformation Technique for Null Space-Based Linear Discriminant Analysis with Lagrange Method," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 2, pp. 208-212, 2013. DOI: .

[ACM Style]

Yuxi Hou, Hwang-Ki Min, Iickho Song, Myeong Soo Choi, Sun Park, and Seong Ro Lee. 2013. Transformation Technique for Null Space-Based Linear Discriminant Analysis with Lagrange Method. The Journal of Korean Institute of Communications and Information Sciences, 38, 2, (2013), 208-212. DOI: .

[KICS Style]

Yuxi Hou, Hwang-Ki Min, Iickho Song, Myeong Soo Choi, Sun Park, Seong Ro Lee, "Transformation Technique for Null Space-Based Linear Discriminant Analysis with Lagrange Method," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 2, pp. 208-212, 2. 2013.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880