Title :
Blind identification and source separation in 2×3 under-determined mixtures
Author_Institution :
Lab., Univ. of Nice, Sophia Antipolis, France
Abstract :
Under-determined mixtures are characterized by the fact that they have more inputs than outputs, or, with the antenna array processing terminology, more sources than sensors. The problem addressed is that of identifying and inverting the mixture, which obviously does not admit a linear inverse. Identification is carried out with the help of tensor canonical decompositions. On the other hand, the discrete distribution of the sources is utilized for performing the source extraction, the under-determined mixture being either known or unknown. The results presented in this paper are limited to two-dimensional (2-D) mixtures of three sources.
Keywords :
antenna arrays; antenna theory; array signal processing; blind source separation; higher order statistics; identification; 2D mixtures; antenna array processing; blind identification; discrete source distribution; high-order statistics; source extraction; source separation; tensor canonical decomposition; under determined mixture; Array signal processing; Sensor arrays; Sensor phenomena and characterization; Signal processing algorithms; Source separation; Statistical distributions; Tensile stress; Terminology; Two dimensional displays; Vectors;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2003.820073