This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...
In this paper we investigate the regularization property of Kernel Principal Component Analysis (KPCA), by studying its application as a preprocessing step to supervised learning ...
Abstract—We address the problem of maximizing the minimum signal to interference and noise ratio of individual users via linear precoding in a multiuser downlink channel with mul...
Albrecht J. Fehske, Fred Richter, Gerhard Fettweis
This paper presents an algorithm for computing the distance between a point and a convex cone in n-dimensional space. The convex cone is specified by the set of all nonnegative com...
Structured Hidden Markov Model (S-HMM) is a variant of Hierarchical Hidden Markov Model that shows interesting capabilities of extracting knowledge from symbolic sequences. In fact...