GROUPTHRESH Group thresholding
Usage: xo=groupthresh(xi,lambda);
GROUPTHRESH(x,lambda) performs group thresholding on x, with
threshold lambda. x must be a two-dimensional array, the first
dimension labelling groups, and the second one labelling members. This
means that the groups are the row vectors of the input (the vectors
along the 2nd dimension).
Several types of grouping behaviour are available:
GROUPTHRESH(x,lambda,'group') shrinks all coefficients within a given
group according to the value of the l^2 norm of the group in
comparison to the threshold lambda. This is the default.
GROUPTHRESH(x,lambda,'elite') shrinks all coefficients within a
given group according to the value of the l^1 norm of the
group in comparison to the threshold value lambda.
GROUPTHRESH(x,lambda,dim) chooses groups along dimension
dim. The default value is dim=2.
GROUPTHRESH accepts all the flags of THRESH to choose the
thresholding type within each group and the output type (full / sparse
matrix). Please see the help of THRESH for the available
options. Default is to use soft thresholding and full matrix output.
References:
M. Kowalski. Sparse regression using mixed norms. Appl. Comput. Harmon.
Anal., 27(3):303--324, 2009.
M. Kowalski and B. Torresani. Sparsity and persistence: mixed norms
provide simple signal models with dependent coefficients. Signal, Image
and Video Processing, 3(3):251--264, 2009.
G. Yu, S. Mallat, and E. Bacry. Audio Denoising by Time-Frequency Block
Thresholding. IEEE Trans. Signal Process., 56(5):1830--1839, 2008.
Url: http://ltfat.github.io/doc/sigproc/groupthresh.html
See also: thresh, demo_audioshrink.
Package: ltfat