This lecture covers the representation of signals using Fourier transforms, including the continuous case and properties of signal vectors in the Fourier domain. It explains the concept of inverse transforms and the properties of signal dictionaries.
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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.
