This lecture covers the Fourier transform, focusing on compression techniques and spectral analysis. It discusses the compression of images using different ratios and the analysis of periodic signals through Fourier series.
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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.
