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Covers matrix operations, Fourier transformations, Gaussian models, and signal representations using algebraic methods.
Covers the calculation of Fourier coefficients for periodic complex signals and the concept of a complete orthonormal system.
Introduces signal processing basics, Fourier transform, and filtering techniques with practical applications and challenges.
Covers the properties of signal/data representations using Fourier transformations and matrices.
Explores representing analog signals digitally through sampling and quantization, discussing sampling frequency, undersampling consequences, and the stroboscopic effect.
Explores Fourier filtering principles, applications in image processing, and efficient FFT implementation.
