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Explores the history and efficiency of the fast Fourier transform algorithm, demonstrating its practical applications and computational advantages.
Explores neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.
Covers matrix operations, Fourier transformations, Gaussian models, and signal representations using algebraic methods.
Explains the Fast Fourier Transform, a fast algorithm for calculating the Discrete Fourier Transform.
