# modwptdetails

Maximal overlap discrete wavelet packet transform details

## Syntax

## Description

returns
the maximal overlap discrete wavelet packet transform (MODWPT) details for the
1-D signal, `w`

= modwptdetails(`x`

)`x`

. The MODWPT details provide zero-phase
filtering of the signal. By default, `modwptdetails`

returns
only the terminal nodes, which are at level 4 or at level
`floor(log2(numel(x)))`

, whichever is smaller.

**Note**

To decide whether to use `modwptdetails`

or
`modwpt`

, consider the
type of data analysis you need to perform. For applications that require
time alignment, such as nonparametric regression analysis, use
`modwptdetails`

. For applications where you want
to analyze the energy levels in different packets, use
`modwpt`

. For more information, see Algorithms.

`[`

returns a vector of transform
levels corresponding to the rows of `w`

,`packetlevs`

]
= modwptdetails(___)`w`

.

`[`

returns `w`

,`packetlevs`

,`cfreq`

]
= modwptdetails(___)`cfreq`

, the
center frequencies of the approximate passbands corresponding to the MODWPT
details in `w`

.

`[___] = modwptdetails(___,FullTree=`

,
where `tf`

)`tf`

is `false`

, returns details about
only the terminal (final-level) wavelet packet nodes. If you specify
`true`

, then `modwptdetails`

returns
details about the full wavelet packet tree down to the default or specified
level. The default value for `tf`

is
`false`

.

## Examples

## Input Arguments

## Output Arguments

## Algorithms

The MODWPT details (`modwptdetails`

) are
the result of zero-phase filtering of the signal. The features in
the MODWPT details align exactly with features in the input signal.
For a given level, summing the details for each sample returns the
exact original signal.

The output of the MODWPT (`modwpt`

)
is time delayed compared to the input signal. Most filters used to
obtain the MODWPT have a nonlinear phase response, which makes compensating
for the time delay difficult. All orthogonal scaling and wavelet filters
have this response, except the Haar wavelet. It is possible to time
align the coefficients with the signal features, but the result is
an approximation, not an exact alignment with the original signal.
The MODWPT partitions the energy among the wavelet packets at each
level. The sum of the energy over all the packets equals the total
energy of the input signal.

## References

[1] Percival, Donald B., and Andrew T. Walden. *Wavelet Methods for Time Series
Analysis*. Cambridge Series in Statistical and Probabilistic Mathematics.
Cambridge ; New York: Cambridge University Press, 2000.

[2] Walden, A. T., and A. Contreras Cristan. “The Phase–Corrected Undecimated Discrete
Wavelet Packet Transform and Its Application to Interpreting the Timing of Events.”
*Proceedings of the Royal Society of London. Series A: Mathematical,
Physical and Engineering Sciences* 454, no. 1976 (August 8, 1998):
2243–66. https://doi.org/10.1098/rspa.1998.0257.

## Extended Capabilities

## Version History

**Introduced in R2016a**