Adaptive filter output using dsp.FrequencyDomain​AdaptiveFilt

A general outline for using the dsp.FrequencyDomainAdaptiveFilter in MATLAB to remove background noise from EMI measurement data.

A general approach to using the `dsp.FrequencyDomainAdaptiveFilter` in MATLAB to remove background noise from EMI measurement data. Here are the key steps:

1. Load and preprocess the EMI measurement data: Load the data and perform any necessary preprocessing steps, such as normalization or DC removal.
2. Set up the adaptive filter: Define the filter length and step size for the adaptive filter.
3. Initialize variables: Create variables to store the output signal (denoised signal) and the error signal (residual noise).
4. Process the signals in blocks: If the data is large, process it in blocks to manage memory constraints.
5. Apply the adaptive filter: Use the `dsp.FrequencyDomainAdaptiveFilter` to filter the background noise from the input signal.
6. Visualize the results: Plot the FFT (Fast Fourier Transform) of the input signal and the denoised signal to compare the frequency content.
7. Analyze the results: Carefully examine the results and adjust the filter parameters if necessary.

The code provides a starting point and can be adapted to handle specific data and requirements.