Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
In this paper we describe two methods for estimating the motion parameters of an image sequence. For a sequence of images, the global motion can be described by ???? independent m...
Recent advances have been reported in detecting and estimating the location of more than one target within a single monopulse radar beam. Successful tracking of those targets has ...