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The Partial Least Squares(PLS) is a novel multivariate data analysis method developed from practical applications in real world. It is not influenced by the total scatter matrices of training samples being singular or not. So PLS can efficiently deal with the case of high-dimensional space with only small sample size such as biological feature recognition. The standard PLS firstly reshapes images...
This paper studies efficient complex valued matrix manipulations for multi-user STBC-MIMO decoding. A novel method called Alamouti blockwise analytical matrix inversion (ABAMI) is proposed for the inversion of large complex matrices that are based on Alamouti sub-blocks. Another method using a variant of Givens rotation is proposed for fast QR decomposition of this kind of matrices. Our solutions...
In this letter, we present a method of two-dimensional canonical correlation analysis (2D-CCA) where we extend the standard CCA in such a way that relations between two different sets of image data are directly sought without reshaping images into vectors. We stress that 2D-CCA dramatically reduces the computational complexity, compared to the standard CCA. We show the useful behavior of 2D-CCA through...
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