Explores psychoacoustics, signal processing, and the brain's interpretation of sound frequencies, covering topics like the Missing Fundamental phenomenon and the inner workings of the cochlea.
Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.
Covers the Fast Fourier Transform (FFT) algorithm and its applications in computational physics, including image processing, experimental techniques, filters, and analysis of microscopy images.
Covers the properties of the Discrete-Time Fourier Transform, including linearity, shifts, time reversal, differentiation, convolution, conjugate symmetry, and Parseval's Relation.
Explores the discrete-time Fourier transform, its properties, and signal transformations, including examples like the rectangular pulse and unit impulse.
