A HYBRID METHOD FOR BLIND SIGNAL DE-NOISING VIA INDEPENDENT COMPONENT ANALYSIS
Alessandra Budillon, Francesco Palmieri and Rosario Varriale
e-mail: falebudil,frapalmig@unina.it,rosvarri@tin.it
This paper presents a signal de-noising method based on the
extraction of two independent components. Two FIR lters
are adapted blindly and forced to produce outputs which are
as independent as possible through time. Various cost func-
tions are considered ranging from linear correlation to non
linear correlation and joint entropy. The typical presence of
a large number of local minima in the various cost functions
has suggested a hybrid approach that trades computational
complexity with solution accuracy. Two experiments on
speech corrupted by independent noise and the separation
of two AR processes are presented.