This course introduces computational aspects of signal processing, specifically algorithms for processing digital signals, methods for the design and analysis of signal processing algorithms, architectures for signal processing systems, and areas of application. Topics include signal analysis (signal definition, time and frequency domains, sampling and digitizing, noise and error), systems for signal processing (filters and nonfilters, correlation, adaptation), and algorithms and architectures (fast Fourier transforms, fast convolution, digital filtering, interpolation and resampling, digital signal processors, function evaluation, and computational complexity). Areas of application include communication systems, speech signal processing, and digital media.
Course prerequisites: 
Knowledge of complex numbers and linear algebra.
Course instructor: 
Sadowsky, Marks

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