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Denoise signal using multiscale local 1-D polynomial transform

specifies `y`

= mlptdenoise(___,`Name,Value`

)`mlpt`

properties
using one or more `Name,Value`

pair arguments,
and any of the previous syntaxes

`[`

also returns the thresholded
multiscale local 1–D polynomial transform coefficients.`y`

,`T`

,`thresholdedCoefs`

]
= mlptdenoise(___)

`[`

also returns the original
multiscale local 1–D polynomial transform coefficients.`y`

,`T`

,`thresholdedCoefs`

,`originalCoefs`

]
= mlptdenoise(___)

Maarten Jansen developed the theoretical foundation of the multiscale
local polynomial transform (MLPT) and algorithms for its efficient
computation [1][2][3]. The MLPT uses a lifting scheme, wherein a kernel
function smooths fine-scale coefficients with a given bandwidth to
obtain the coarser resolution coefficients. The `mlpt`

function uses only local polynomial
interpolation, but the technique developed by Jansen is more general
and admits many other kernel types with adjustable bandwidths [2].

[1] Jansen, Maarten. “Multiscale Local Polynomial Smoothing in a Lifted
Pyramid for Non-Equispaced Data.” *IEEE Transactions on Signal
Processing* 61, no. 3 (February 2013): 545–55.
https://doi.org/10.1109/TSP.2012.2225059.

[2] Jansen, Maarten, and Mohamed Amghar. “Multiscale Local Polynomial
Decompositions Using Bandwidths as Scales.” *Statistics and
Computing* 27, no. 5 (September 2017): 1383–99.
https://doi.org/10.1007/s11222-016-9692-8.

[3] Jansen, Maarten, and Patrick Oonincx. *Second Generation
Wavelets and Applications*. London ; New York: Springer,
2005.