Detecting periodicities
Abstract
Chapter 6, Detecting Periodicities, is about spectral analysis, the procedures used to represent data as a superposition of harmonically varying components and to detect periodicities. The key concept is the Fourier series, a type of linear model in which the data are represented by a mixture of sinusoidally varying components. The chapter aims to make the student completely comfortable with the discrete Fourier transform (DFT), the key algorithm used in studying periodicities. Theoretical analysis and a practical discussion of MatLab's DFT function are closely interwoven.
Keywords
sinusoidal; periodicity; amplitude; sampling theorem; Fourier series; Fourier transform; fast Fourier transform; Nyquist frequency; ...
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