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Based on the principle of Principal component analysis (PCA), we present an unsupervised dimensionality reduction method called PLS2-B which using X instead of Y in the regression of Partial least squares (PLS). we proved that the number of PLS2-B latent variables is equal to the components of PLS2-B and is equal to the principal components of PCA, PLS2-B and PCA will be completely equivalent, and...
Somatosensory evoked potential (SEP) usually contains a set of detailed temporal components measured and identified in time domain, providing meaningful information on physiological mechanisms of the nervous system. The purpose of this study is to reveal complex and fine time-frequency features of SEP in time-frequency domain using advanced time-frequency analysis (TFA) and pattern classification...
Gait is a potential behavioral feature, and many allied studies have demonstrated that it can be served as a useful biometric feature for recognition. This paper described a novel gait recognition technique based on support vector machine fusion of contour projection and skeleton model features. A principal component analysis method was used to lower the dimension of contour projection after segmenting...
This paper presents an approach for compression and synthesis of BTF (bidirectional texture function), and using it BTF can be mapped on arbitrary surfaces. BTF is a kind of multidimensional texture data, which can perfectly shows the self-shadow, self-occlusion and inter-reflection reflectance of object surfaces under varying light directions. However, it is difficult to use BTF on object surfaces...
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