A first-course in signal processing with applications in computer music and audio for students comfortable with high-school algebra, calculus, complex variables, and beginning linear algebra. The lectures cover fundamentals of audio signal processing such as sinusoids, spectra, Fourier transforms, Laplace transform, z transform, linear time-invariant filters, digitizing systems, transfer-function analysis, and basic Fourier analysis in the continuous and discrete-time cases. Python is used for in-class demonstrations and homework/lab assignments. The labs focus on practical applications of the theory, with emphasis on working with waveforms and spectra, ''getting sound'', and developing proficiency in the Python language. See http://ccrma.stanford.edu/courses/MUSIC 320/.
2-4 units · Letter (ABCD/NP)
A first-course in signal processing with applications in computer music and audio for students comfortable with high-school algebra, calculus, complex variables, and beginning linear algebra. The lectures cover fundamentals of audio signal processing such as sinusoids, spectra, Fourier transforms, Laplace transform, z transform, linear time-invariant filters, digitizing systems, transfer-function analysis, and basic Fourier analysis in the continuous and discrete-time cases. Python is used for in-class demonstrations and homework/lab assignments. The labs focus on practical applications of the theory, with emphasis on working with waveforms and spectra, ''getting sound'', and developing proficiency in the Python language. See http://ccrma.stanford.edu/courses/320/.
Offered in Autumn 2026 at Stanford University.