Computes the 1D wavelet packet (WP) decomposition and stores the resulting coefficients and wavelet packet tree information in the wavelet packet structure. Wire data to the signal input to determine the polymorphic instance to use or manually select the instance.

Use the pull-down menu to select an instance of this VI.


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WA WP Decomposition Details

The following illustration shows a full decomposition of the wavelet packet tree at level 3:

The black numbers indicate the path of each node, and the red numbers show the index of each node. The path is a combination of the characters 0 and 1, where 0 represents lowpass filtering, and 1 represents highpass filtering. For example, a value of 101 indicates that this VI passes the signal through a highpass filter, through a lowpass filter, and then through a highpass filter.

The discrete wavelet decomposition and the arbitrary path decomposition are two special cases of the wavelet packet decomposition. You can decompose the approximation coefficients and the detail coefficients in the wavelet packet decomposition. The discrete wavelet decomposition implements the analysis filtering only on the approximation coefficients. However, you can apply analysis filtering to the approximation or the detail in the arbitrary path decomposition.

Examples

Refer to the following VIs for examples of using the WA WP Decomposition VI:

  • Wavelet Packet - Plot Tree VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • Wavelet Packet - Read and Write Coefficients VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • Wavelet Packet - Read Entropy VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • Wavelet Packet - Join Node VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • Wavelet Packet - Split Node VI: labview\examples\Wavelet Analysis\WAGettingStarted
  • Wavelet Packet Signal Compression VI: labview\examples\Wavelet Analysis\WAApplications