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Matlab ExperimentsMatlab Experiments
Convolution
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GoalGoal
We are going to write Matlab programsWe are going to write Matlab programs using convolution to perform calculations of sine wave and squares inputs applied toof sine wave and squares inputs applied to two low pass filters: an ideal low pass filter and an non-ideal filter using a simple RCand an non ideal filter using a simple RC circuit.
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Impulse Response h(t)Impulse Response h(t)
• The impulse response to the Non-Ideal LowThe impulse response to the Non Ideal Low Pass (RC) filter is
11( ) ( )t
RCh−
• The impulse response to an Ideal Low Pass
1( ) ( )RCh t e u tRC
=
The impulse response to an Ideal Low Pass filter is
( ) 2 sinc(2 ) -c ch t f f t tπ= ∞ < < ∞
• See the Appendix for details
where is the cutoff frequencycf
See the Appendix for details
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Experiments1. Write a Matlab program to calculate the output for each of the types
f f Cof filters: Ideal and RC. 2. The inputs will be sine and square waves. 3. The impulse responses are those given for each type of program.4 The cutoff frequencies should be the same for each filter4. The cutoff frequencies should be the same for each filter5. The frequencies used for each of the input signals should be the
same.6. Perform at least (more would be preferable) 3 experiments for the ( p ) p
sine wave input and at least (more would be preferable) 3 experiments for the square wave input for each of the two filters.
a) Input frequency is less than the cutoffb) Input frequency is around the cutoffb) put eque cy s a ou d t e cutoc) Several where the Input frequency is greater than the cutoffd) For the Ideal filter case with the square wave input find the frequency where
the output is undistorted7. The output of the program should plot the input signal, the impulse p p g p p g , p
response, and the output signal. It should also display the cutoff frequency of the filter and the frequency of the input signal.
8. Write a professional report which includes the Matlab code used for the Ideal and RC filters the Matlab outputs for each of thethe Ideal and RC filters, the Matlab outputs for each of the experiments, an explanation of the results, and comparison of the performance of these filters.
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ExamplesExamples1. RC Filter
A. Input: Sine Wavei. input frequency < cutoff frequency.
5
10
Signals Cutoff Frequency 1.5915 Signal Frequency 0.5
-1 0 1 2 3 4 5
0
Time (Seconds)Convolution
-0 5
0
0.5
1
0 1 2 3 4 5 6 7 8 9 10-1
0.5
Time (Seconds)
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ExamplesExamples1. RC Filter
A. Input: Sine Waveii. input frequency close to the cutoff frequency.
5
10
Signals Cutoff Frequency 1.5915 Signal Frequency 1.5
-1 0 1 2 3 4 5
0
Time (Seconds)
1Convolution
-0.5
0
0.5
1
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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ExamplesExamples1. RC Filter
A. Input: Sine Waveiii. input frequency > cutoff frequency.
5
10
Signals Cutoff Frequency 1.5915 Signal Frequency 5
-1 0 1 2 3 4 5
0
Time (Seconds)
1Convolution
-1
-0.5
0
0.5
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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ExamplesExamples1. RC Filter
A. Input: Sine Waveiv. input frequency >> cutoff frequency.
5
10
Signals Cutoff Frequency 1.5915 Signal Frequency 25
-1 0 1 2 3 4 5
0
Time (Seconds)
1Convolution
-0.5
0
0.5
1
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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ExamplesExamples1. RC Filter
B. Input: Square Wavei. input frequency < cutoff frequency.
5
10
Signals Cutoff Frequency 1.5915 Signal Frequency 0.5
-1 0 1 2 3 4 5
0
Time (Seconds)
1Convolution
-0.5
0
0.5
1
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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ExamplesExamples1. RC Filter
B. Input: Square Waveii. input frequency close to the cutoff frequency.
5
10
Signals Cutoff Frequency 1.5915 Signal Frequency 1.5
-1 0 1 2 3 4 5
0
5
Time (Seconds)Convolution
-0 5
0
0.5
1Convolution
0 1 2 3 4 5 6 7 8 9 10-1
0.5
Time (Seconds)
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ExamplesExamples1. RC Filter
B. Input: Sine Waveiii. input frequency > cutoff frequency.
5
10
Signals Cutoff Frequency 1.5915 Signal Frequency 5
-1 0 1 2 3 4 5
0
Time (Seconds)Convolution
0 5
0
0.5
1Convolution
0 1 2 3 4 5 6 7 8 9 10-1
-0.5
Time (Seconds)
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ExamplesExamples1. RC Filter
B. Input: Square Waveiv. input frequency >> cutoff frequency.
5
10
Signals Cutoff Frequency 1.5915 Signal Frequency 25
-1 0 1 2 3 4 5
0
Time (Seconds)
1Convolution
-1
-0.5
0
0.5
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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ExamplesExamples2. Ideal Filter
A. Input: Sine Wavei. input frequency < cutoff frequency.
1
2
3
Signals Cutoff Frequency 1.5915 Signal Frequency 0.5
-1 0 1 2 3 4 5-1
0
Time (Seconds)Convolution
-0.5
0
0.5
1
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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ExamplesExamples2. Ideal Filter
A. Input: Sine Waveii. input frequency close to the cutoff frequency.
1
2
3
Signals Cutoff Frequency 1.5915 Signal Frequency 1.5
-1 0 1 2 3 4 5-1
0
1
Time (Seconds)Convolution
0 5
0
0.5
1Convolution
0 1 2 3 4 5 6 7 8 9 10-1
-0.5
Time (Seconds)
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ExamplesExamples2. Ideal Filter
A. Input: Sine Waveiii. input frequency > cutoff frequency.
1
2
3
Signals Cutoff Frequency 1.5915 Signal Frequency 5
-1 0 1 2 3 4 5-1
0
Time (Seconds)Convolution
-0.5
0
0.5
1
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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ExamplesExamples2. Ideal Filter
B. Input: Square Wavei. input frequency < cutoff frequency.
2
3
Signals Cutoff Frequency 1.5915 Signal Frequency 0.5
-1 0 1 2 3 4 5-1
0
1
Time (Seconds)Time (Seconds)
0
0.5
1Convolution
0 1 2 3 4 5 6 7 8 9 10-1
-0.5
Time (Seconds)
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ExamplesExamples2. Ideal Filter
B. Input: Square Waveii. input frequency close to the cutoff frequency.
1
2
3
Signals Cutoff Frequency 1.5915 Signal Frequency 1.5
-1 0 1 2 3 4 5-1
0
1
Time (Seconds)Convolution
0 5
0
0.5
1Convolution
0 1 2 3 4 5 6 7 8 9 10-1
-0.5
Time (Seconds)
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ExamplesExamples2. Ideal Filter
B. Input: Sine Waveiii. input frequency > cutoff frequency.
1
2
3
Signals Cutoff Frequency 1.5915 Signal Frequency 5
-1 0 1 2 3 4 5-1
0
Time (Seconds)Convolution
-0.5
0
0.5
1
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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ExamplesExamples2. Ideal Filter
B. Input: Square Waveiv. input frequency << cutoff frequency.
1
2
3
Signals Cutoff Frequency 1.5915 Signal Frequency 0.1
-1 0 1 2 3 4 5-1
0
Time (Seconds)Convolution
-0.5
0
0.5
1
0 1 2 3 4 5 6 7 8 9 10-1
Time (Seconds)
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Some HintsSome Hints
• Remember the “conv” is a discreteRemember the conv is a discrete function and so the result must be multiplied by the sampling periodmultiplied by the sampling period.
• For the impulse response for the Ideal FilterFilter
1. Be careful on how you program its value for t=0.2 Recognize that h(t) is valid for all values of t2. Recognize that h(t) is valid for all values of t.
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Appendix:RC L P FilRC Low Pass Filter
c ri idVout Vin Vouti C i
=− Vin
R
1k
C Vouti
1( )
c rdVout Vin Vouti C i
dt RdVout Vout VinC
dt R RVinC V t
= = =
+ =
+
C 1n Voutir ic
1( )
1 10;
at
pC VoutR R
Vout Ae B
pC pR RC
−
+ =
= +
+ = =
1
1
1 1
j CVout VinR
j C
V
ω
ω
=+
1
1
(0) 0
tRC
tRC
CB Vin
Vout Ae Vin
Vout Ae Vin
−
−
=
= +
= = +
2
1 11 1 ( )
1The cutoff (radian) frequency is defined as .c
VoutVin j CR CR
RC
ω ω
ω
= =+ +
=
1
1
(0) 0
(1 ) ( )
RC
tRC
t
Vout Ae VinA Vin
Vout Vin e u t−
−
= = += −
= −
RC
1(1 ) ( )( ) (1 ) ( ) ((t
RC tRCd e u th t e t
dtδ
−−= = − − −
1 11 1) ) ( ) ( )t t
RC RCe u t e u tRC RC
− −=
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AppendixId l L P FilIdeal Low Pass Filter
It can be shown that the impulse response to an ideal low pass filter is( ) 2 sinc(2 ) here is the c toff freq enc and the "sinc" f nction is gi en as:
c ch t f f t tf
π= −∞ < < ∞where is the cutoff frequency and the "sinc" function is given as:
sin( )sinc( )
cfxx
x=
|H(f)|
fc f