Hi Luke Megonigal,
To guide you in filter design for feature engineering in signals, consider the following tools/function in MATLAB:
1. Filter Design Tools in MATLAB:
- "designfilt" Function: MATLAB provides the "designfilt" function, which allows for the design of digital filters based on specifications you provide. This function is versatile and supports various filter types and design methods.
- Filter Designer App: For a more interactive approach, MATLAB's Filter Designer app provides a graphical interface for designing and analyzing filters. It can be particularly useful if you're exploring different filter designs and their effects on your signal.
2. Feature Extraction Using Filtered Signals:
- Once you have designed a suitable filter, apply it to your signal using the "filter" function in MATLAB. Analyze the filtered signal to identify features of interest, such as peaks, which can be detected using the "findpeaks" function.
- Consider extracting various statistical features from the filtered signal, such as mean, standard deviation, skewness, and kurtosis, which might be relevant for your classification or regression models.
Iterative Design and Validation: Filter design for feature engineering is often an iterative process. You may need to experiment with different filter types, parameters, and extracted features to find the combination that provides the most discriminative or predictive power for your application.
References for further exploration:
- For detailed guidance on designing digital filters, refer to the documentation of the "designfilt" function: https://www.mathworks.com/help/signal/ref/designfilt.html
- To learn more about the Filter Designer app and how it can be used for interactive filter design, see: https://in.mathworks.com/help/dsp/ref/filterdesigner.html
- For information on detecting peaks in your signal, which can be an important feature, refer to the documentation of the "findpeaks" function: https://www.mathworks.com/help/signal/ref/findpeaks.html
Hope this helps!
