Decimated and nondecimated 1-D wavelet transforms,
1-D dual-tree transforms, wavelet packets, lifting

Analyze signals using discrete wavelet transforms, dual-tree transforms, wavelet packets, and lifting methods.

`wavedec` |
Multilevel 1-D wavelet decomposition |

`waverec` |
Multilevel 1-D wavelet reconstruction |

`dwt` |
Single-level discrete 1-D wavelet transform |

`idwt` |
Single-level inverse discrete 1-D wavelet transform |

`appcoef` |
1-D approximation coefficients |

`detcoef` |
1-D detail coefficients |

`dwtmode` |
Discrete wavelet transform extension mode |

`haart` |
Haar 1-D wavelet transform |

`ihaart` |
Inverse 1-D Haar wavelet transform |

`lwt` |
1-D lifting wavelet transform |

`ilwt` |
Inverse 1-D lifting wavelet transform |

`lwtcoef` |
Extract or reconstruct 1-D LWT wavelet coefficients |

`upcoef` |
Direct reconstruction from 1-D wavelet coefficients |

`wrcoef` |
Reconstruct single branch from 1-D wavelet coefficients |

`upwlev` |
Single-level reconstruction of 1-D wavelet decomposition |

`wenergy` |
Energy for 1-D wavelet or wavelet packet decomposition |

`wmaxlev` |
Maximum wavelet decomposition level |

`wpdec` |
Wavelet packet decomposition 1-D |

`wprec` |
Wavelet packet reconstruction 1-D |

`wpcoef` |
Wavelet packet coefficients |

`wprcoef` |
Reconstruct wavelet packet coefficients |

`bestlevt` |
Best level tree wavelet packet analysis |

`besttree` |
Best tree wavelet packet analysis |

`depo2ind` |
Node depth-position to node index |

`ind2depo` |
Node index to node depth-position |

`plot` |
Plot tree GUI |

`wpspectrum` |
Wavelet packet spectrum |

`wpsplt` |
Split (decompose) wavelet packet |

`wpjoin` |
Recompose wavelet packet |

`wpfun` |
Wavelet packet functions |

`otnodes` |
Order terminal nodes of binary wavelet packet tree |

`wenergy` |
Energy for 1-D wavelet or wavelet packet decomposition |

`modwt` |
Maximal overlap discrete wavelet transform |

`imodwt` |
Inverse maximal overlap discrete wavelet transform |

`modwtmra` |
Multiresolution analysis based on MODWT |

`modwtcorr` |
Multiscale correlation using the maximal overlap discrete wavelet transform |

`modwtvar` |
Multiscale variance of maximal overlap discrete wavelet transform |

`modwtxcorr` |
Wavelet cross-correlation sequence estimates using the maximal overlap discrete wavelet transform (MODWT) |

`swt` |
Discrete stationary wavelet transform 1-D |

`iswt` |
Inverse discrete stationary wavelet transform 1-D |

`modwpt` |
Maximal overlap discrete wavelet packet transform |

`imodwpt` |
Inverse maximal overlap discrete wavelet packet transform |

`modwptdetails` |
Maximal overlap discrete wavelet packet transform details |

`dddtree` |
Dual-tree and double-density 1-D wavelet transform |

`dddtreecfs` |
Extract dual-tree/double-density wavelet coefficients or projections |

`dtfilters` |
Analysis and synthesis filters for oversampled wavelet filter banks |

`idddtree` |
Inverse dual-tree and double-density 1-D wavelet transform |

`plotdt` |
Plot dual-tree or double-density wavelet transform |

`wvarchg` |
Find variance change points |

`measerr` |
Approximation quality metrics |

`wavemngr` |
Wavelet manager |

`dyaddown` |
Dyadic downsampling |

`dyadup` |
Dyadic upsampling |

`allnodes` |
Tree nodes |

`get` |
WPTREE contents |

`isnode` |
Existing node test |

`istnode` |
Terminal nodes indices test |

`entrupd` |
Entropy update (wavelet packet) |

`nodejoin` |
Recompose node |

`nodesplt` |
Split (decompose) node |

`tnodes` |
Determine terminal nodes |

`wpviewcf` |
Plot wavelet packets colored coefficients |

`cfs2wpt` |
Wavelet packet tree construction from coefficients |

`wptree` |
WPTREE constructor |

`wp2wtree` |
Extract wavelet tree from wavelet packet tree |

`wpcutree` |
Cut wavelet packet tree |

`dtree` |
DTREE constructor |

`ntree` |
NTREE constructor |

`treeord` |
Tree order |

`write` |
Write values in WPTREE fields |

`read` |
Read values of WPTREE |

`set` |
WPTREE field contents |

`disp` |
WPTREE information |

**Critically-Sampled Wavelet Reconstruction**

Understand how to reconstruct signals from wavelet transformed data.

**1-D Decimated Wavelet Transforms**

View a summary and examples of 1-D critically-sampled discrete wavelet transform.

**Haar Transforms for Time Series Data and Images**

Use Haar transforms to analyze signal variability, create signal approximations, and watermark images.

**Fast Wavelet Transform (FWT) Algorithm**

Learn about the fast wavelet transform.

**Critically Sampled and Oversampled Wavelet Filter Banks**

Learn about tree-structured, multirate filter banks.

**1-D Wavelet Coefficient Selection Using the Wavelet Analyzer
App**

Choose 1-D wavelet coefficients using the interactive Wavelet Analyzer app.

**Analytic Wavelets Using the Dual-Tree Wavelet Transform**

Create approximately analytic wavelets using the dual-tree complex wavelet transform.

**1-D Stationary Wavelet Transform**

Use the stationary wavelet transform to analyze, decompose, reconstruct, and denoise 1-D signals.

**Wavelet Cross-Correlation for Lead-Lag Analysis**

Measure the similarity between two signals at different scales.

**Nondecimated Discrete Stationary Wavelet Transforms (SWTs)**

Use the stationary wavelet transform to restore wavelet translation invariance.

**Critically Sampled and Oversampled Wavelet Filter Banks**

Learn about tree-structured, multirate filter banks.

Compensate for discrete wavelet transform border effects using zero padding, symmetrization, and smooth padding.

Learn about 1-D signal extension and truncation.

**Density Estimation Using Wavelets**

Use wavelets for nonparametric probability density estimation.

**1-D Fractional Brownian Motion Synthesis**

Synthesize a 1-D fractional Brownian motion signal.

Use wavelet to characterize local signal regularity using wavelet leaders.

Use wavelet packets indexed by position, scale, and frequency for wavelet decomposition of 1-D and 2-D signals.

Analyze a signal with wavelet packets using the Wavelet Analyzer app.

Analyze an image with wavelet packets using the Wavelet Analyzer app.

View examples showing how to add your own wavelet tree objects.

**Examples Using Wavelet Packet Tree Objects**

Learn how to use wavelet packet trees.

**Objects in the Wavelet Toolbox Software**

View a summary of objects provided in the toolbox.

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