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Page 1: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 2: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 3: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 4: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 5: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 6: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 7: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 8: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 9: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 10: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 11: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 12: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600
Page 13: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

ECE 697 Delta-Sigma Converters Design

Lecture#4 Slides

Vishal Saxena([email protected])

Page 14: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

Spectral Estimation

Page 15: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

Coherent Sampling

0 5 10 15 20 25 30 35 40 45 50-1

-0.5

0

0.5

1

samples (n)

x[n]

100 200 300 400 500 600 700 800 900 1000-350

-300

-250

-200

-150

-100

-50

0

FFT bins (k)

20*lo

g 10|X

(k)|,

dB

file:FFTdemo1.m

Page 16: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

Non-Coherent Sampling : FFT leakage

100 200 300 400 500 600 700 800 900 1000-350

-300

-250

-200

-150

-100

-50

0

FFT bins (k)

20*lo

g 10|X

(k)|,

dB

129129.01129.001

file:FFTdemo2.m

Page 17: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

FFT leakage contd.

file:FFTdemo2.m

100 200 300 400 500 600 700 800 900 1000

-120

-100

-80

-60

-40

-20

FFT bins (k)

20*lo

g 10|X

(k)|,

dB

129129.01129.001

Page 18: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

Spectral Windows

5 10 15 20 25 300

0.2

0.4

0.6

0.8

1

Samples

Ampl

itude

Time domain

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9-150

-100

-50

0

50

Normalized Frequency ( rad/sample)

Mag

nitu

de (d

B)

Frequency domain

Rectangular#1BartlettHann

% Compare Rect, Bartlett and Hann windows

L = 32;

wvtool(rectwin(L), bartlett(L), ds_hann(L));

Page 19: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

Spectral Windows contd.

5 10 15 20 25 300

0.2

0.4

0.6

0.8

1

Samples

Ampl

itude

Time domain

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9-140

-120

-100

-80

-60

-40

-20

0

20

40

Normalized Frequency ( rad/sample)M

agni

tude

(dB)

Frequency domain

Blackman-HarrisHann

% Compare Blackman-Harris and Hann windows

L = 32;

wvtool(blackmanharris(L), ds_hann(L));

Page 20: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

FFT with Windowing

file:FFTdemo_windowing.m

100 200 300 400 500 600 700 800 900 1000-200

-150

-100

-50

0

50

100

FFT bins (k)

20*lo

g 10|X

(k)|,

dB

RectHannBlackman-Harris

Page 21: › courses › ECE615 › s16 › Lecture Notes › … · ©VishalSaxena Coherent Sampling 0 5 10 15 20 25 30 35 40 45 50-1-0.5 0 0.5 1 samples (n) x[n] 100 200 300 400 500 600

© Vishal Saxena

References

[1] S. Pavan, N. Krishnapura, “EE658 VLSI Data Conversion Circuits Course,” 2008, [Online]: http://www.ee.iitm.ac.in/~nagendra/videolectures/doku.php?id=start