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Denoise signal using multiscale local 1-D polynomial transform

`y = mlptdenoise(x,t)`

`y = mlptdenoise(x,t,numLevel)`

`y = mlptdenoise(___,Name,Value)`

```
[y,T] =
mlptdenoise(___)
```

```
[y,T,thresholdedCoefs]
= mlptdenoise(___)
```

```
[y,T,thresholdedCoefs,originalCoefs]
= mlptdenoise(___)
```

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, M. "Multiscale Local Polynomial
Smoothing in a Lifted Pyramid for Non-Equispaced Data". *IEEE
Transactions on Signal Processing*, Vol. 61, Number 3,
2013, pp. 545–555.

[2] Jansen, M., and M. Amghar. "Multiscale
local polynomial decompositions using bandwidths as scales". *Statistics
and Computing* (forthcoming). 2016.

[3] Jansen, M., and Patrick Oonincx. *Second
Generation Wavelets and Applications*. London: Springer,
2005.

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