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Continuous-time Signal Sampling









Prof. Siripong Potisuk

Why Sampling



 Necessary for digital processing of analog signals,

e.g., x(t)

 Taking snapshots of x(t) every Ts seconds

 Each snapshot is called a sample

 Ts is the so-called sampling interval, i.e., the time

interval between each sample (second/sample)

 Prefer regularly spaced samples, though not

necessary

Why Sampling



 The sequence of samples is given by



x[n]  x(nTs ), n  I

1

 FS  is the sampling frequency or rate

Ts

 The unit of sampling frequency is samples/second,

but often expressed in terms of Hz to match the

highest frequency in Hz of the analog signal

Sampling Interval Selection



 By sampling, we throw out a lot of information in

between samples

 A set of samples can represent more than one distinct

signal

Sampling Interval Selection



 Given a set of sampling points, under what

conditions can we reconstruct the original CT

signals from which those samples came?

 In other words, all values of x(t) between sampling

points are lost because of sampling

 Need to consider the frequency contents of the CT

signal being sampled  Fourier Transform

Impulse Sampling

Frequency-Domain Analysis of Sampling



Using the Multiplication property of CTFT,

FT



  











2

where and S  2 Fs 

T





Thus,

Frequency-Domain Analysis of Sampling



Assuming x(t) is band-limited, i.e.,

X ( j)  0,   M









No overlap between shifted

spectra!

Reconstruction of the CT signal from its samples



If there is no overlap between

shifted spectra, we can use a

lowpass filter to reconstruct the

original CT signal









Original Spectrum Reconstructed Spectrum

Nyquist Sampling Theorem

Let x(t ) be a band - limited signal such that

X ( j )  0,   M .

Then, x(t ) is uniquely determined by its samples

x(nT ), n  I if

 s  2 M  Nyquist rate

2

where  S   sampling frequencyand

T

M  Nyquist frequency.

Practical Sampling

Aliasing Effect

Distortion of filtered spectrum caused by Aliasing

Common Samples obtained from sampling two

sinusoids of different frequencies

Anti-aliasing Filter

• Band-limiting operation done on the analog

signal before sampling to prevent aliasing

• Passing it through an analog lowpass filter, e.g.

Butterworth, Chebyshev, Elliptical

• Alternatively called Guard Filter

• Remove all frequency components outside the

range [-Fc, Fc] where Fc < fd

Signal Reconstruction

• Three interpolation Methods

• Band-limited interpolation

• Zero-order Hold interpolation

• First-order Hold Interpolation (linear)

Band-limited Interpolation in the Time Domain

Zero-order Hold Interpolation









t

h0 (t )   [ ( )   (  T )]d

0



 u (t )  u (t  T )

First-order Hold Interpolation



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