Digital Signal Processing Reference
In-Depth Information
Figure 2.11 Estimated source signal constellations obtained by jade (a) and GUT
method gut5 (b) for the data with four outliers. Signals that correspond to outliers are
marked by triangle. Robust GUT method gut5 is unaffected by outliers, which are
clearly detected in the plots whereas jade fails completely: outliers are able to
destroy the patterns of BPSK and 8-QAM signals.
To illustrate the reliable performance of the robut GUT matrices under contami-
nation, four observations were replaced by an outlier z out generated as
z out ¼ ( b 1 u 1 z 1, max , ... , b 4 u 4 z 4, max ) T
where z i ,max is the element of the i th row of the sample data matrix Z n ¼ ( z 1 ... z n ) [
C
kn with largest modulus, u i Unif(1,5) and b i is a rva with a value of 2 1 or 1 with
equal probability 2 .Notethat z i , out ¼ b i u i z i ,max points to the same or opposite direc-
tion as z i ,max but its magnitude is at least as big, but at most 5 times larger than that
of z i ,max . Note that only 0.2 percent (4 observations out of n ¼ 2000) of the data is
contaminated. Figure 2.11 depicts the estimated source signal constellations obtained
by jade and gut5 . As can be seen, only gut5 is able to separate the sources and is unaf-
fected by outliers, which are clearly detected in the plots. jade on the other hand fails
completely: BPSK and 8-QAM sources are no longer discernible in the plots. The
reliable performance of the robust ICA methods is evident in Table 2.2.: only the
robust GUT methods gut4 and gut5 and the robust DOGMA estimator d1 are able
to separate the sources.
Table 2.3 gives average computation times. As can be seen gut1 (i.e., the SUT) and
fobi are the fastest to compute whereas fica is the slowest. To compute fobi we used the
 
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