Multisignal 1-D compression thresholds and performances
[THR_VAL,L2_Perf,N0_Perf] = mswcmptp(DEC,METH)
[THR_VAL,L2_Perf,N0_Perf] = mswcmptp(DEC,METH,PARAM)
[THR_VAL,L2_Perf,N0_Perf] = mswcmptp(DEC,METH) or
= mswcmptp(DEC,METH,PARAM) computes the vectors
after a compression using the
METH method and,
if required, the
PARAM parameter (see
mswcmp for more information on
For the ith signal:
THR_VAL(i) is the threshold applied
to the wavelet coefficients. For a level dependent method,
the threshold applied to the detail coefficients at level
L2_Perf(i) is the percentage of
energy (L2_norm) preserved after compression.
N0_Perf(i) is the percentage of
zeros obtained after compression.
You can use three more optional inputs:
[...] = mswcmptp(...,S_OR_H,KEEPAPP,IDXSIG)
S_OR_H ('s' or 'h') stands for
soft or hard thresholding (see
KEEPAPP (true or false) indicates
whether to keep approximation coefficients (
or not (
IDXSIG is a vector which contains
the indices of the initial signals, or the character vector
The defaults are, respectively,
% Load original 1D-multisignal. load thinker % Perform a decomposition at level 2 using wavelet db2. dec = mdwtdec('r',X,2,'db2'); % Compute compression thresholds and exact performances % obtained after a compression using the method 'N0_perf' and % requiring a percentage of zeros near 95% for the wavelet % coefficients. [THR_VAL,L2_Perf,N0_Perf] = mswcmptp(dec,'N0_perf',95);
Daubechies, I. (1992), Ten lectures on wavelets, CBMS-NSF conference series in applied mathematics. SIAM Ed.
Mallat, S. (1989), “A theory for multiresolution signal decomposition: the wavelet representation,” IEEE Pattern Anal. and Machine Intell., vol. 11, no. 7, pp. 674–693.
Meyer, Y. (1990), Ondelettes et opérateurs, Tome 1, Hermann Ed. (English translation: Wavelets and operators, Cambridge Univ. Press. 1993.)