Signal Processing with MATLAB

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Signal Processing with MATLAB provided by MATLAB Academy is a comprehensive online course, which lasts for 7 hours worth of material. Signal Processing with MATLAB is taught by Renee Bach. Upon completion of the course, you can receive an e-certificate from MATLAB Academy. The course is taught in Englishand is Free Certificate. Visit the course page at MATLAB Academy for detailed price information.

Overview
    • Introduction: Familiarize yourself with the course.
    • Generating Signals and Common Signal Operations: Generate different types of sampled signals. Perform operations in the time-domain like changing the sample rate of a signal or shifting the frequency content without introducing unwanted artifacts.
    • Estimating Power Spectral Density: Estimate the power spectrum of signals with different frequency components. Explore standard techniques to improve the accuracy of your estimation.
    • Improving the Power Spectral Density Estimate: Explore different spectral analysis techniques to improve results for noisy, time-varying, or short signals.
    • Characterizing Digital Filters: Visualize filter characteristics in different domains to understand how a filter will modify the time-domain and frequency-domain of your signals.
    • Designing Digital Filters: Design digital FIR and IIR filters using common filter response types. Start with a set of specifications or a preferred design algorithm.
    • Streaming Signal Processing: Process streaming signals by dividing input data into frames and processing each frame as it is acquired.
    • Conclusion: Learn next steps and give feedback on the course.

Syllabus
    • Course Overview
    • Signal Processing Basics
    • Course Example - Digital Watermarking
    • Generate Digital Signals
    • Resampling
    • Modulation
    • Review - Generating Signals and Common Signal Operations
    • Course Example - Identifying Fan Faults
    • Discrete Fourier Transform
    • Periodogram
    • Zero Padding
    • Windowing
    • Review - Estimating Power Spectral Density
    • Course Example - Real-World Issues
    • Welch Method
    • Time-Frequency Analysis
    • Parametric and Subspace Methods
    • Review - Improving the Power Spectral Density Estimate
    • Course Example - Underwater Sound Absorption
    • Filter Coefficients
    • Filter Responses
    • Filter Delay
    • Zeros and Poles
    • Review - Characterizing Digital Filters
    • Course Example - Verify Watermark
    • FIR Filters
    • IIR Filters
    • Filter Design Algorithms
    • Arbitrary Filter Response
    • Review - Designing Digital Filters
    • Course Example - Monitoring Fan
    • Create DSP System Objects
    • Process Signals in a Loop
    • Review - Streaming Signal Processing
    • Additional Resources
    • Survey