DWT

Compute discrete wavelet transform (DWT) of input or decompose signals into subbands with smaller bandwidths and slower sample rates

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Libraries:
DSP System Toolbox / Transforms

Description

You can configure this block to compute the Discrete Wavelet Transform (DWT) of the input signal or decompose the signal into subbands with smaller bandwidths and slower sample rates. The block uses a series of highpass and lowpass FIR filters to repeatedly divide the input frequency range, as illustrated in Multilevel Filter Banks (the Asymmetric one).

You can specify the filter bank highpass and lowpass filters by providing vectors of filter coefficients. You can do so directly on the block mask. If you have a Wavelet Toolbox™ license, you can specify wavelet-based filters by selecting a wavelet from the Filter parameter. You must set the filter bank structure to asymmetric or symmetric, and specify the number of levels in the filter bank.

For the same input, the DWT configuration of this block does not produce the same results as the Wavelet Toolbox dwt function. Because DSP System Toolbox™ is designed for real-time implementation and Wavelet Toolbox is designed for analysis, the products handle boundary conditions and filter states differently. To make the output of the dwt function match the DWT output of this block, complete the following steps:

1. Set the boundary condition of the dwt function to zero-padding. To do so, type dwtmode('zpd') at the MATLAB^® command line.

2. To match the latency of the block (implemented using FIR filters), add zeros to the input of the dwt function. The number of zeros you add must be equal to the half-length of the filter.

Note

The DWT block is same as the Dyadic Analysis Filter Bank block with different default settings. For more information on block ports and parameters, see the Dyadic Analysis Filter Bank block reference page.

Examples

Wavelet Reconstruction and Noise Reduction

Uses the Dyadic Analysis Filter Bank and Dyadic Synthesis Filter Bank blocks to show both the perfect reconstruction property of wavelets and an application for noise reduction.

• Open Script

Block Characteristics

Data Types	double | single
Multidimensional Signals	No
Variable-Size Signals	No

References

[1] Fliege, N. J. Multirate Digital Signal Processing: Multirate Systems, Filter Banks, Wavelets. West Sussex, England: John Wiley & Sons, 1994.

[2] Strang, G. and T. Nguyen. Wavelets and Filter Banks. Wellesley, MA: Wellesley-Cambridge Press, 1996.

[3] Vaidyanathan, P. P. Multirate Systems and Filter Banks. Englewood Cliffs, NJ: Prentice Hall, 1993.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using Simulink® Coder™.

Generated code relies on the memcpy or memset function (string.h) under certain conditions.

Version History

Introduced before R2006a