BLIND SEPARATION OF N BINARY SOURCES FROM ONE OBSERVATION: A DETERMINISTIC APPROACH
Konstantinos I. Diamantaras, Efthymia Chassioti
kdiamant@it.teithe.gr
We show that it is possible to separate n ? 1 binary source
signals from a single linear mixture, under very mild as
sumptions, based on the clustering of the data. We develop
the mathematical treatment of the problem and propose
a recursive, finite algorithm for its solution. The applica
tion of this method is only limited by the level of noise and
by the combinatorial explosion as the number of sources
n increases since the algorithm complexity is exponential
w.r.t. n. Simulation results indicate that the method can
successfully separate as many as 10 sources from a single
mixture in a few seconds on a typical desktop PC.