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Sampling Theory

The dual of the Poisson Summation Formula is the continuous-time aliasing theorem, which lies at the foundation of elementary sampling theory [243, Appendix G]. If $ x(t)$ denotes a continuous-time signal, its sampled version $ x(nT)$, $ n\in{\bf Z}$, is associated with the continuous-time signal

$\displaystyle x_d(t)
\isdef x(t)\psi_T(t)
\isdef x(t)\sum_m\delta(t-mT).
$

where $ T$ denotes the (fixed) sampling interval in seconds. The sampled signal values $ x(nT)$ are thus treated mathematically as coefficients of impulses at the sampling instants. Taking the Fourier transform gives

\begin{eqnarray*}
X_d(f) &=& \hbox{\sc FT}_f(x\cdot\psi_T) = X\ast \Psi_T\\
&=&...
...ac{1}{T}X\ast \psi_{1/T}
= f_s\sum_{k=-\infty}^{\infty}X(f-kf_s)
\end{eqnarray*}

where $ f_s\isdef 1 f_s\isdef 1/T$ denotes the sampling rate in radians per second. Note that $ X_d(f)$ is periodic with period $ f_s$. We see that if $ X(f)$ is bandlimited to less than $ f_s$ radians per second, i.e., if $ X(f)=0$ for all $ \vert f\vert\geq f_s/2$, then only the $ k=0$ term will be nonzero in the summation over $ k$, and this means there is no aliasing. The terms $ X(f-kf_s)$ for $ k\neq 0$ are all aliasing terms.


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Next: The Uncertainty Principle

written by Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See http://ccrma.stanford.edu/~jos/ for details.


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