Main Content

Filter Frames of a Noisy Sine Wave Signal in Simulink

This example shows how to lowpass filter a noisy signal in Simulink® and visualize the original and filtered signals with a spectrum analyzer. For a MATLAB® version of this example, see Filter Frames of a Noisy Sine Wave Signal in MATLAB.

Open Model

To create a new blank model and open the library browser:

  1. On the MATLAB Home tab, click Simulink, and choose the Basic Filter model template.

  2. Click Create Model to create a basic filter model opens with settings suitable for use with DSP System Toolbox™. To access the library browser, in the Simulation tab, click Library Browser on the model toolstrip.

Basic filter model template contains two Sine Wave blocks, one Gaussian Noise block, one Lowpass FIR Filter block, and one spectrum Analyzer block. The two Sine Wave blocks and the Gaussian Noise block feed into an adder. The output of the adder block is the noisy sinusoidal signal. This noisy signal is fed into the Lowpass Filter block. The output of the Lowpass Filter block is the filtered signal. The noisy signal and the filtered signal are fed into the Spectrum Analyzer which shows the spectra of both the signals.

The new model using the template settings and contents appears in the Simulink Editor. The model is only in memory until you save it.

Inspect Model

Input Signal

Three source blocks comprise the input signal. The input signal consists of the sum of two sine waves and white Gaussian noise with mean 0 and variance 0.05. The frequencies of the sine waves are 1 kHz and 15 kHz. The sampling frequency is 44.1 kHz. The dialog box shows the block parameters for the 1 kHz sine wave.

The block dialog box of the first Sine Wave block. The settings on the block dialog are as follows. Main pane: Amplitude is set to 1, Frequency is set to 1000 Hz, Phase offset is set to 0 radians, Sample mode is set to Discrete, Output complexity is set to Real, Computation method is set to Trignometric fcn, Sample time is set to 1/44100, Samples per frame is set to 256, Resetting states when re-enabled is set to Restart at time zero.

Lowpass Filter

The lowpass filter is modeled using a Lowpass Filter block. The example uses a generalized Remez FIR filter design algorithm. The filter has a passband frequency of 8000 Hz, a stopband frequency of 10,000 Hz, a passband ripple of 0.1 dB, and a stopband attenuation of 80 dB.

The block dialog box of the Lowpass Filter block. The settings on the block dialog are as follows. Main pane: Filter type is set to FIR, Design minimum order filter check box is selected, Passband edge frequency is set to 8000 Hz, Stopband edge frequency is set to 10000 Hz, Maximum passband ripple is set to 0.1 dB, Minimum stopband attenuation is set to 80 dB, Inherit sample rate from input check box is not selected, Input sample rate is set to 44100 Hz, Simulate using is set to Interpreted execution.

The Lowpass Filter block uses frame-based processing to process data one frame at a time. Each frame of data contains sequential samples from an independent channel. Frame-based processing is advantageous for many signal processing applications because you can process multiple samples at once. By buffering your data into frames and processing multisample frames of data, you can improve the computational time of your signal processing algorithms.

Compare Original and Filtered Signal

Use a Spectrum Analyzer to compare the power spectra of the original and filtered signals. The spectrum units are in dBm.

To run the simulation, in the model, click Run. To stop the simulation, in the Spectrum Analyzer block, click Stop. Alternatively, you can execute the following code to run the simulation for 200 frames of data.

set_param(model,'StopTime','256/44100 * 200')

Output of the Spectrum Analyzer shows two signals. Original signal in yellow is unattenuated and has peaks at 1 KHz and 15 KHz. Filtered signal in blue is attenuated after 10 KHz.

Frequencies above 10 kHz in the source signal are attenuated. The resulting signal maintains the peak at 1 kHz because it falls in the passband of the lowpass filter.