The Orthogonal Frequency Division Multiple Access (OFDMA) when used in wireless networks provides high spectral efficiency with robust performance and thus been considered for 4G air interface technology. On the other hand, the MIMO technique that uses multiple antennas at the base station and the mobile station provides spatial diversity and multiplexing gain. Adaptive Resource Allocation tech...

This chapter is about eigenvalues and singular values of matrices. Computational algorithms and sensitivity to perturbations are both discussed. An eigenvalue and eigenvector of a square matrix A are a scalar λ and a nonzero vector x so that Ax = λx. A singular value and pair of singular vectors of a square or rectangular matrix A are a nonnegative scalar σ and two nonzero vectors u and v so th...

Latent Semantic Analysis, when used for automated essay grading, makes use of document word count vectors for scoring the essays against domain knowledge. Words in the domain knowledge documents and essays are counted, and Singular Value Decomposition is undertaken to reduce the dimensions of the semantic space. Near neighbour vector cosines and other variables are used to calculate an essay sc...

We consider a clustering problem where we observe feature vectors Xi ∈ R, i = 1, 2, . . . , n, from K possible classes. The class labels are unknown and the main interest is to estimate them. We are primarily interested in the modern regime of p n, where classical clustering methods face challenges. We propose Influential Features PCA (IF-PCA) as a new clustering procedure. In IF-PCA, we select...

Mitral valve regurgitation (MVR) is a common valvular disease in dogs. Hydrokinetic evaluation of the blood flow within the ventricles has become possible by vector flow mapping (VFM), which shows the blood flow within the ventricles in vector and vortex flows. Blood flow within the left ventricle of MVR dogs was compared at different stages of MVR and to that of normal dogs. 14 normal dogs and...

We consider a clustering problem where we observe feature vectors Xi ∈ R, i = 1, 2, . . . , n, from K possible classes. The class labels are unknown and the main interest is to estimate them. We are primarily interested in the modern regime of p n, where classical clustering methods face challenges. We propose Important Features PCA (IF-PCA) as a new clustering procedure. In IFPCA, we select a ...

We derive a quantum deformation of the WN algebra and its quantum Miura transformation, whose singular vectors realize the Macdonald polynomials.