Estimate the signal from its noisy observation using a linear filter designed by minimizing the mean square error (Wiener Filter)
Input Parameters:
Input Signal(s): Specify the type of signal (sine, cosine, amplitude modulated (AM) signal, or double sideband suppressed carrier signal) from the dropdown options, and enter the frequency values of the signal(s).
Sampling Frequency (in Hz): Enter the sampling frequency in the input field.
Filter Order: Enter the order of the Wiener filter.
SNR (in dB): Enter the desired Signal-to-Noise Ratio (SNR) in decibels (dB).
Steps:
1. Generate Reference Signal:
Click the “Generate Reference Signal” button to generate the reference signal.
2. Generate Noisy Input Signal:
Click the “Generate Noisy Input Signal” button to add Additive White Gaussian Noise (AWGN) to the reference signal and generate the noisy signal.
3. Display Power Spectral Density (PSD) of the Noisy and Estimated Signals:
Click the “Show PSD for Noisy Signal” and “Show PSD for Estimated Signal” buttons to visualize the PSD of the noisy signal and the estimated signal, respectively.
4. Compute Wiener Filter Coefficients:
Click the “Compute Filter Coefficients” button to compute and visualize the Wiener filter coefficients, which minimize the error between the estimated signal and the reference signal.
5. Generate the Estimated Signal:
Click the “Generate Estimated Signal” button to visualize the estimated signal produced by the Wiener filter.
6. Generate the Residual Signal:
Click the “Generate Residual Signal” button to display the difference between the reference and the estimated signal.
7. Compare the Reference Signal and the Estimated Signal:
Click the “Compare” button to visualize the comparison between the reference signal and the estimated signal.
