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Sampling and Reconstruction of Signals Lecture 3
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Lecture 3 Sampling and Reconstruction of Signals

Mar 19, 2022

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Page 1: Lecture 3 Sampling and Reconstruction of Signals

Sampling and Reconstruction

of Signals

Lecture 3

Page 2: Lecture 3 Sampling and Reconstruction of Signals

Sampling

To use digital signal processing techniques on continuous-time signals, we need to them into a sequence of numbers. This is done by taking samples of the analog signal periodically (one evert T seconds):

The sampling frequency has to be large enough so that the signal can be recovered from the samples x[n]. The limit is the Nyquist rate that is twice the highest frequency of the analog signal. That is, if the highest frequency of the signal is B Hz. the sampling rate need to be greater than (or at least equal to) 2B samples per second.

Page 3: Lecture 3 Sampling and Reconstruction of Signals

Sampling

If the signal is an aperiodic signal with finite energy, its spectrum is:

And it can be recovered from its spectrum using:

Page 4: Lecture 3 Sampling and Reconstruction of Signals

Sampling

The spectrum of a discrete-time signal is:

Or equivalently,

Page 5: Lecture 3 Sampling and Reconstruction of Signals

Sampling

The signal x[n] can be recovered from the spectrum:

The relationship beteen time in analog domain (t) and digital domain (n) is:

Page 6: Lecture 3 Sampling and Reconstruction of Signals

Sampling

In fact x[n] represents a sequence of samples of the analog signal at time nT:

So,

The relationship between analog and digital frequencies is:

Page 7: Lecture 3 Sampling and Reconstruction of Signals

Sampling

Substituting in in the equality in the previous slide, we get:

So,

The right-hand side can be written as,

Page 8: Lecture 3 Sampling and Reconstruction of Signals

Sampling

We observe that in the interval to is identical to

in the interval /2 to /2, so:

We have used the fact that

Page 9: Lecture 3 Sampling and Reconstruction of Signals

Sampling Comparing the equations in the previous two slides, we get,

Or equivalently,

So if 2 , that is, if the sampling rate exceeds the Nyquist rate, the analog signal, then the analog signal can be recovered from the samples,

Page 10: Lecture 3 Sampling and Reconstruction of Signals

Reconstruction Given the sampled signals spectrum X(f), we get,

From Fourier transform,

We have

Page 11: Lecture 3 Sampling and Reconstruction of Signals

Reconstruction

Page 12: Lecture 3 Sampling and Reconstruction of Signals

Aliasing:

Page 13: Lecture 3 Sampling and Reconstruction of Signals

Reconstruction:

Page 14: Lecture 3 Sampling and Reconstruction of Signals

Reconstruction:

Page 15: Lecture 3 Sampling and Reconstruction of Signals

Sampling (Nyquist) Theorem

Page 16: Lecture 3 Sampling and Reconstruction of Signals

Sampling: Example

Speech Signals mainly contain components in frequencies less that 3400 Hz. So, 6800 samples per second is the minimum sampling rate. To make reconstruction easier (less sharp filters) 8000 samples are taken per second. That is one sample every 1 (micro-seconds).

Audio contains frequencies up to 20 kHz. So minimum is 40,000 samples/sec. Usually 44.1 k samples are taken each second.

Video: The number of samples for a video signal depends on the number of pixels (picture elements) per frame and the number of frames per second.

Page 17: Lecture 3 Sampling and Reconstruction of Signals

Discrete-Processing of Analog Signals

First the analog signal is digital signal using Analog-to-Digital (A to D or A/D) converter, then it is processed by the Discrete-Time (most often Digital) system and then reconverted to Analog using D/A converter.

Page 18: Lecture 3 Sampling and Reconstruction of Signals

Quantization

Page 19: Lecture 3 Sampling and Reconstruction of Signals

Quantization

Page 20: Lecture 3 Sampling and Reconstruction of Signals

Quantization

Page 21: Lecture 3 Sampling and Reconstruction of Signals

Quantization Error

Page 22: Lecture 3 Sampling and Reconstruction of Signals

Quantization Error : Example