# mswden

(Not recommended) Multisignal 1-D denoising using wavelets

`mswden`

is not recommended. Use `wdenoise`

instead.

## Syntax

## Description

`mswden`

computes thresholds and, depending on the selected
option, performs denoising of 1-D signals using wavelets.

`[`

returns a denoised version `xd`

,`decden`

,`thresh`

] = mswden("den",`dec`

,`meth`

,`param`

)`xd`

of the multisignal `x`

whose wavelet decomposition is `dec`

. `meth`

is the name
of the denoising method and `param`

is the associated parameter, if
required. `decden`

is the wavelet decomposition of the denoised signal, and
`thresh`

are the threshold values.

## Examples

## Input Arguments

## Output Arguments

## References

[1] Birgé, L., and P. Massart. “From
Model Selection to Adaptive Estimation.” *Festschrift for Lucien Le Cam: Research
Papers in Probability and Statistics* (E. Torgersen, D. Pollard, and G. Yang, eds.).
New York: Springer-Verlag, 1997, pp. 55–88.

[2] DeVore, R. A., B. Jawerth, and B. J.
Lucier. “Image Compression Through Wavelet Transform Coding.” *IEEE
Transactions on Information Theory*. Vol. 38, Number 2, 1992, pp.
719–746.

[3] Donoho, D. L. “Progress in
Wavelet Analysis and WVD: A Ten Minute Tour.” *Progress in Wavelet Analysis and
Applications* (Y. Meyer, and S. Roques, eds.). Gif-sur-Yvette: Editions Frontières,
1993.

[4] Donoho, D. L., and I. M. Johnstone.
“Ideal Spatial Adaptation by Wavelet Shrinkage.” *Biometrika*.
Vol. 81, pp. 425–455, 1994.

[5] Donoho, D. L., I. M. Johnstone, G.
Kerkyacharian, and D. Picard. “Wavelet Shrinkage: Asymptopia?” *Journal
of the Royal Statistical Society*, *series B*, Vol. 57, No. 2,
pp. 301–369, 1995.

[6] Donoho, D. L., and I. M. Johnstone.
“Ideal denoising in an orthonormal basis chosen from a library of bases.”
*C. R. Acad. Sci. Paris*, *Ser. I*, Vol. 319, pp.
1317–1322, 1994.

[7] Donoho, D. L. “De-noising by
Soft-Thresholding.” *IEEE Transactions on Information Theory*. Vol.
42, Number 3, pp. 613–627, 1995.

[8] Mesa, Hector. “Adapted Wavelets for
Pattern Detection.” In *Progress in Pattern Recognition, Image Analysis and
Applications*, edited by Alberto Sanfeliu and Manuel Lazo Cortés, 3773:933–44.
Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. https://doi.org/10.1007/11578079_96.

## Version History

**Introduced in R2007a**