This lecture covers the properties of signal/data representations using Fourier transformations, orthogonal matrices, and circulant matrices. The slides discuss the mathematical concepts and operations involved in signal processing.
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Covers the Fourier transform, its properties, applications in signal processing, and differential equations, emphasizing the concept of derivatives becoming multiplications in the frequency domain.
Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.
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.
