
Learn how to perform signal processing in MATLAB® and Signal Processing Toolbox™ using real-life examples.
Prerequisites: MATLAB Fundamentals and Signal Processing Onramp
Familiarize yourself with the course.
Generate different types of sampled signals. Perform operations in the time domain, such as changing the sample rate of a signal or shifting the frequency content without introducing unwanted artifacts.
Estimate the power spectrum of signals with different frequency components. Explore standard techniques to improve the accuracy of your estimation.
Explore different spectral analysis methods to improve results for noisy, time-varying, or short signals.
Visualize filter characteristics in different domains to understand how a filter will modify the time domain and frequency domain of your signals.
Design digital FIR and IIR filters using common filter response types. Start with a set of specifications or a preferred design algorithm.
Process streaming signals by dividing input data into frames and processing each frame as it is acquired.
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An interactive introduction to practical signal processing methods for spectral analysis.
Learn core MATLAB functionality for data analysis, modeling, and programming.
Learn the theory and practice of building deep neural networks with real-life image and sequence data.