6. Detecting periodicities
6.1 Describing sinusoidal oscillations103
6.2 Models composed only of sinusoidal functions105
6.3 Going complex112
6.4 Lessons learned from the integral transform114
6.5 Normal curve115
6.6 Spikes116
6.7 Area under a function118
6.8 Time-delayed function118
6.9 Derivative of a function120
6.10 Integral of a function120
6.11 Convolution121
6.12 Nontransient signals122
Problems124
References125
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 ...
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