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 neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.
Covers the Fast Fourier Transform (FFT) algorithm and its applications in computational physics, including image processing, experimental techniques, filters, and analysis of microscopy images.
Explores the discrete-time Fourier transform, its properties, and signal transformations, including examples like the rectangular pulse and unit impulse.
