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Covers examples of Discrete Fourier Transform calculations for different signals and frequencies.
Explores the analysis and classification of texture in images, emphasizing the role of Machine Learning techniques like Convolutional Neural Networks.
Explains the Fast Fourier Transform, a fast algorithm for calculating the Discrete Fourier Transform.
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 the Discrete Fourier Transform as a change of basis and the implications of having orthogonal vectors as a basis for complex numbers.
