This lecture explains the effect of convolving any spectrum by the Fourier transform of a rectangular window. The instructor illustrates how the convolution process works, emphasizing the importance of the main lobe size and its impact on the resulting signal.
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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.
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.
