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This lecture covers the properties and applications of Fourier transforms, including elementary properties, convolution theorem, Parseval's theorem, and energy spectral density. It explains how Fourier transforms are used in solving PDEs and signal processing, with a focus on non-periodic functions. The lecture also delves into the concept of energy spectral density and its relation to self-convolution, providing insights into the distribution of energy in different wavelengths.