Note: This page has been translated by MathWorks. Please click here

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

The following sections guide you through the process of calculating
the channel latencies required for perfect wavelet reconstruction.
This example uses the `ex_wavelets`

model, but
you can apply the process to perform perfect wavelet reconstruction
in any model. To open the example model, type `ex_wavelets`

at the MATLAB^{®} command
line.

You must have a Wavelet
Toolbox™ product license to run the `ex_wavelets`

model.

Before you can begin calculating the latencies required for perfect wavelet reconstruction, you must know the types of filters being used in your model.

The Dyadic Analysis Filter Bank and the Dyadic Synthesis Filter
Bank blocks in the `ex_wavelets`

model have the
following settings:

**Filter**=`Biorthogonal`

**Filter order [synthesis/analysis]**=`[3/5]`

**Number of levels**=`3`

**Tree structure**=`Asymmetric`

**Input**=`Multiple ports`

Based on these settings, the Dyadic Analysis Filter Bank and
the Dyadic Synthesis Filter Bank blocks
construct biorthogonal filters using the Wavelet
Toolbox `wfilters`

function.

Once you know the types of filters being used by the Dyadic
Analysis and Dyadic Synthesis Filter Bank blocks, you need to calculate
the group delay of those filters. To do so, you can use the Signal
Processing Toolbox™ `fvtool`

.

Before you can use `fvtool`

, you must first
reconstruct the filters in the MATLAB workspace. To do so, type
the following code at the MATLAB command line:

`[Lo_D, Hi_D, Lo_R, Hi_R] = wfilters('bior3.5')`

Where `Lo_D`

and `Hi_D`

represent
the low- and high-pass filters used by the Dyadic Analysis Filter
Bank block, and `Lo_R`

and `Hi_R`

represent
the low- and high-pass filters used by the Dyadic Synthesis Filter
Bank block.

After you construct the filters in the MATLAB workspace,
you can use `fvtool`

to determine the group delay
of the filters. To analyze the low-pass biorthogonal filter used by
the Dyadic Analysis Filter Bank block, you must do the following:

Type

`fvtool(Lo_D)`

at the MATLAB command line to launch the Filter Visualization Tool.When the Filter Visualization Tool opens, click the Group delay response button () on the toolbar, or select

**Group Delay Response**from the**Analysis**menu.

Based on the Filter Visualization Tool's analysis, you can see that the group delay of the Dyadic Analysis Filter Bank block's low-pass biorthogonal filter is 5.5.

Repeat this procedure to analyze the group delay of each of
the filters in your model. This section does not show the results
for each filter in the `ex_wavelets`

model because
all wavelet filters in this particular example have the same group
delay.

To determine the delay introduced by the analysis and synthesis filter bank system, you must reconstruct the tree structures of the Dyadic Analysis Filter Bank and the Dyadic Synthesis Filter Bank blocks. To learn more about constructing tree structures for the Dyadic Analysis Filter Bank and Dyadic Synthesis Filter Bank blocks, see the following sections of the DSP System Toolbox™ User's Guide:

Because the filter blocks in the `ex_wavelets`

model
use biorthogonal filters with three levels and an asymmetric tree
structure, the filter bank system appears as shown in the following
figure.

The extra delay values
of *M* and *N* on paths 3 and 4
in the previous figure ensure that the total delay on each of the
four filter paths is identical.

Now that you have reconstructed the filter bank system, you can calculate the delay on each filter path. To do so, use the following Noble identities:

You can apply the Noble identities by summing the delay on each signal path from right to left. The first Noble identity indicates that moving a delay of 1 before a downsample of 2 is equivalent to multiplying that delay value by 2. Similarly, the second Noble identity indicates that moving a delay of 2 before an upsample of 2 is equivalent to dividing that delay value by 2.

The `fvtool`

analysis in step 1 found that
both the low- and high-pass filters of the analysis filter bank have
the same group delay (*F _{0}* =

The following figure shows the filter bank system with the intermediate delay sums displayed below each path.

You can see from the previous figure that the signal delays
on paths 1 and 2 are identical: 7(*F*+*G*).
Because each path of the filter bank system has identical delay, you
can equate the delay equations for paths 3 and 4 with the delay equation
for paths 1 and 2. After constructing these equations, you can solve
for *M* and *N*, respectively:

$$\begin{array}{l}\text{Path3=Path1}\Rightarrow 4M+3(F+G)=7(F+G)\\ \text{}\Rightarrow M=F+G\\ \\ \text{Path4=Path1}\Rightarrow 2N+(F+G)=7(F+G)\\ \text{}\Rightarrow N=3(F+G)\end{array}$$

The `fvtool`

analysis in step 1 found the group
delay of each biorthogonal wavelet filter in this model to be 5.5
samples. Therefore, *F* = 5.5 and *G* =
5.5. By inserting these values into the two previous
equations, you get *M* = 11 and *N* =
33. Because the total delay on each filter path
must be the same, you can find the overall delay of the filter bank
system by inserting *F* = 5.5 and *G* =
5.5 into the delay equation for any of the four
filter paths. Inserting the values of *F* and *G* into
7(*F*+*G*) yields an overall delay
of 77 samples for the filter bank system of the `ex_wavelets`

model.

Now that you know the latencies required for perfect wavelet
reconstruction, you can incorporate those delay values into the model.
The `ex_wavelets`

model has already been updated
with the correct delay values (*M* = 11, *N* =
33, *Overall* = 77), so it is ready to run.

After you run the model, examine the reconstruction error in
the Difference scope. To further examine any particular areas of interest,
use the zoom tools available on the toolbar of the scope window or
from the **View** menu.

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

Was this topic helpful?