This paper considers the problem of estimating a high dimensional inverse covariance matrix that can be well approximated by "sparse" matrices. Taking advantage of the c...
We show several estimates on the probability distribution of some data at points in real complete intersection varieties: norms of real affine solutions, condition number of real ...
We use prior and boundary estimates as the approximation of outside probability and establish our beam thresholding strategies based on these estimates. Lexical items, e.g. head wo...
Comparative analysis of the threshold SNR and/or sample support values where genuine maximum likelihood DOA estimation starts to produce “outliers” is conducted for unconditio...
In this work we present a point classification algorithm for multi-variate data. Our method is based on the concept of attribute subspaces, which are derived from a set of user sp...