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DSP System Toolbox™ provides several blocks implementing digital filters, such as Discrete FIR Filter and Biquad Filter.

Use these blocks if you have already performed the design and analysis and know your
desired filter coefficients. You can use these blocks to filter single-channel and
multichannel signals, and to simulate floating-point and fixed-point filters. Then, you can
use the Simulink^{®}
Coder™ product to generate highly optimized C code from your filters.

To implement a filter, you must provide the following basic information about the filter:

The desired filter structure

The filter coefficients

**Note**

Use the Digital Filter Design block to design and implement a filter. Use the Discrete FIR Filter and Biquad Filter blocks to implement a pre-designed filter. Both methods implement a filter in the same manner and have the same behavior during simulation and code generation.

Use the Discrete FIR Filter (Simulink) block to implement a lowpass filter:

Define the lowpass filter coefficients in the MATLAB

^{®}workspace by typing`lopassNum = [-0.0021 -0.0108 -0.0274 -0.0409 -0.0266 0.0374 0.1435 0.2465 0.2896 0.2465 0.1435 0.0374 -0.0266 -0.0409 -0.0274 -0.0108 -0.0021];`

Open Simulink and create a new model file.

From the DSP System Toolbox Filtering>Filter Implementations library, click-and-drag a Discrete FIR Filter block into your model.

Double-click the Discrete FIR Filter block. Set the block parameters as follows, and then click

**OK**:**Coefficient source**=`Dialog parameters`

**Filter structure**=`Direct form transposed`

**Coefficients**=`lopassNum`

**Input processing**=`Columns as channels (frame based)`

**Initial states**=`0`

Note that you can provide the filter coefficients in several ways:

Type in a variable name from the MATLAB workspace, such as

`lopassNum`

.Type in filter design commands from Signal Processing Toolbox™ software or DSP System Toolbox software, such as

`fir1(5, 0.2, 'low')`

.Type in a vector of the filter coefficient values.

Rename your block Digital Filter - Lowpass.

The Discrete FIR Filter block in your model now represents a lowpass filter. In the next topic, Implement a Highpass Filter in Simulink, you use a Discrete FIR Filter block to implement a highpass filter. For more information about the Discrete FIR Filter block, see the Discrete FIR Filter (Simulink) block reference page. For more information about designing and implementing a new filter, see Digital Filter Design Block.

In this topic, you implement a highpass filter using the Discrete FIR Filter (Simulink) block:

If the model you created in Implement a Lowpass Filter in Simulink is not open on your desktop, you can open an equivalent model by typing

ex_filter_ex1

at the MATLAB command prompt.

Define the highpass filter coefficients in the MATLAB workspace by typing

hipassNum = [-0.0051 0.0181 -0.0069 -0.0283 -0.0061 ... 0.0549 0.0579 -0.0826 -0.2992 0.5946 -0.2992 -0.0826 ... 0.0579 0.0549 -0.0061 -0.0283 -0.0069 0.0181 -0.0051];

From the DSP System Toolbox Filtering library, and then from the Filter Implementations library, click-and-drag a Discrete FIR Filter block into your model.

Double-click the Discrete FIR Filter block. Set the block parameters as follows, and then click

**OK**:**Coefficient source**=`Dialog parameters`

**Filter structure**=`Direct form transposed`

**Coefficients**=`hipassNum`

**Input processing**=`Columns as channels (frame based)`

**Initial states**=`0`

You can provide the filter coefficients in several ways:

Type in a variable name from the MATLAB workspace, such as

`hipassNum`

.Type in filter design commands from Signal Processing Toolbox software or DSP System Toolbox software, such as

`fir1(5, 0.2, 'low')`

.Type in a vector of the filter coefficient values.

Rename your block Digital Filter - Highpass.

You have now successfully implemented a highpass filter. In the next topic, Filter High-Frequency Noise in Simulink, you use these Discrete FIR Filter blocks to create a model capable of removing high frequency noise from a signal. For more information about designing and implementing a new filter, see Digital Filter Design Block.

In the previous topics, you used Discrete FIR Filter (Simulink) blocks to implement lowpass and highpass filters. In this topic, you use these blocks to build a model that removes high frequency noise from a signal. In this model, you use the highpass filter, which is excited using a uniform random signal, to create high-frequency noise. After you add this noise to a sine wave, you use the lowpass filter to filter out the high-frequency noise:

If the model you created in Implement a Highpass Filter in Simulink is not open on your desktop, you can open an equivalent model by typing

ex_filter_ex2

at the MATLAB command prompt.

If you have not already done so, define the lowpass and highpass filter coefficients in the MATLAB workspace by typing

lopassNum = [-0.0021 -0.0108 -0.0274 -0.0409 -0.0266 ... 0.0374 0.1435 0.2465 0.2896 0.2465 0.1435 0.0374 ... -0.0266 -0.0409 -0.0274 -0.0108 -0.0021]; hipassNum = [-0.0051 0.0181 -0.0069 -0.0283 -0.0061 ... 0.0549 0.0579 -0.0826 -0.2992 0.5946 -0.2992 -0.0826 ... 0.0579 0.0549 -0.0061 -0.0283 -0.0069 0.0181 -0.0051];

Click-and-drag the following blocks into your model file.

Block Library Quantity Add

Simulink / Math Operations library

1

Random Source

Sources

1

Sine Wave

Sources

1

Time Scope

Sinks

1

Set the parameters for the rest of the blocks as indicated in the following table. For any parameters not listed in the table, leave them at their default settings.

Block Parameter Setting Add

**Icon shape**=`rectangular`

**List of signs**=`++`

Random Source

**Source type**=`Uniform`

**Minimum**=`0`

**Maximum**=`4`

**Sample mode**=`Discrete`

**Sample time**=`1/1000`

**Samples per frame**=`50`

Sine Wave

**Frequency (Hz)**=`75`

**Sample time**=`1/1000`

**Samples per frame**=`50`

Time Scope

**File**>**Number of Input Ports**>**3****File**>**Configuration ...**Open the

**Visuals:Time Domain Options**dialog and set**Time span**=`One frame period`

Connect the blocks as shown in the following figure. You may need to resize some of your blocks to accomplish this task.

In the

**Modeling**tab, click**Model Settings**. The**Configuration Parameters**dialog opens.In the

**Solver**pane, set the parameters as follows, and then click**OK**:**Start time**=`0`

**Stop time**=`5`

**Type**=`Fixed-step`

**Solver**=`discrete (no continuous states)`

In the

**Simulation**tab of the model toolstrip, click**Run**.The model simulation begins and the Scope displays the three input signals.

After simulation is complete, select

**View**>**Legend**from the Time Scope menu. The legend appears in the Time Scope window. You can click-and-drag it anywhere on the scope display. To change the channel names, double-click inside the legend and replace the current numbered channel names with the following:Add =

`Noisy Sine Wave`

Digital Filter – Lowpass =

`Filtered Noisy Sine Wave`

Sine Wave =

`Original Sine Wave`

In the next step, you will set the color, style, and marker of each channel.

In the Time Scope window, select

**View**>**Line Properties**, and set the following:Line Style Marker Color Noisy Sine Wave **-****None****Black**Filtered Noisy Sine Wave **-****diamond****Red**Original Sine Wave **None*********Blue**The

**Time Scope**display should now appear as follows:You can see that the lowpass filter filters out the high-frequency noise in the noisy sine wave.

You have now used Discrete FIR Filter blocks to build a model that removes high frequency noise from a signal. For more information about designing and implementing a new filter, see Digital Filter Design Block.

You can specify a static filter using the Discrete FIR Filter (Simulink) or Biquad Filter block. To do so, set the
**Coefficient source** parameter to ```
Dialog
parameters
```

.

For the Discrete FIR Filter, set the **Coefficients** parameter to a
row vector of numerator coefficients. If you set **Filter structure** to
`Lattice MA`

, the **Coefficients** parameter
represents reflection coefficients.

For the Biquad Filter, set the **SOS matrix (Mx6)** to an
*M*-by-6 matrix, where *M* is the number of sections in
the second-order section filter. Each row of the SOS matrix contains the numerator and
denominator coefficients of the corresponding section in the filter. Set **Scale
values** to a scalar or vector of *M*+1 scale values used
between SOS stages.

To change the static filter coefficients during simulation, double-click the block,
type in the new filter coefficients, and click **OK**. You cannot
change the filter order, so you cannot change the number of elements in the matrix of
filter coefficients.

Time-varying filters are filters whose coefficients change with time. You can specify a time-varying filter that changes once per frame. You can filter multiple channels with each filter. However, you cannot apply different filters to each channel; all channels use the same filter.

To specify a time-varying filter using a Biquad Filter block or a Discrete FIR Filter block:

Set the

**Coefficient source**parameter to`Input port(s)`

, which enables extra block input ports for the time-varying filter coefficients.The Discrete FIR Filter block has a

`Num`

port for the numerator coefficients.The Biquad Filter block has

`Num`

and`Den`

ports rather than a single port for the SOS matrix. Separate ports enable you to use different fraction lengths for numerator and denominator coefficients. The scale values port,`g`

, is optional. You can disable the`g`

port by setting**Scale values mode**to`Assume all are unity and optimize`

.

Provide matrices of filter coefficients to the block input ports.

For Discrete FIR Filter block, the number of filter taps,

*N*, cannot vary over time. The input coefficients must be in a 1-by-*N*vector.For Biquad Filter block, the number of filter sections,

*N*, cannot vary over time. The numerator coefficients input,`Num`

, must be a 3-by-*N*matrix. The denominator input coefficients,`Den`

, must be a 2-by-*N*matrix. The scale values input,`g`

, must be a 1-by-(*N*+1) vector.

Use the Biquad Filter block to specify a static biquadratic IIR filter (also known as a second-order section or SOS filter). Set the following parameters:

**Filter structure**—`Direct form I`

, or`Direct form I transposed`

, or`Direct form II`

, or`Direct form II transposed`

**SOS matrix (Mx6)***M*-by-6 SOS matrixThe SOS matrix is an

*M*-by-6 matrix, where*M*is the number of sections in the second-order section filter. Each row of the SOS matrix contains the numerator and denominator coefficients (*b*and_{ik}*a*) of the corresponding section in the filter._{ik}**Scale values**Scalar or vector of*M*+1 scale values to be used between SOS stagesIf you enter a scalar, the value is used as the gain value before the first section of the second-order filter. The rest of the gain values are set to 1.

If you enter a vector of

*M*+1 values, each value is used for a separate section of the filter. For example, the first element is the first gain value, the second element is the second gain value, and so on.

You can use the `ss2sos`

and `tf2sos`

functions from Signal Processing Toolbox software to convert a state-space or transfer function description of your
filter into the second-order section description used by this block.

$$\left[\begin{array}{cccccc}{b}_{01}& {b}_{11}& {b}_{21}& {a}_{01}& {a}_{11}& {a}_{21}\\ {b}_{02}& {b}_{12}& {b}_{22}& {a}_{02}& {a}_{12}& {a}_{22}\\ \vdots & \vdots & \vdots & \vdots & \vdots & \vdots \\ {b}_{0M}& {b}_{1M}& {b}_{2M}& {a}_{0M}& {a}_{1M}& {a}_{2M}\end{array}\right]$$

The block normalizes each row by *a*_{1i} to ensure
a value of 1 for the zero-delay denominator coefficients.