ECET 350 Entire Course NEW

DEVRY ECET 350Week 1 iLab Sallen-Key Active
Filter Design NEW
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http://www.uopassignments.com/ecet-350-
devry/ecet-350-week-1-ilab-sallen-key-active-
filter-design-recent
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Laboratory Title: Sallen-Key Active Filter Design
Objectives:
• Design and simulate a Butterworth, low-pass
Sallen-Key active filter.
• Construct and test the designed Butterworth,
low-pass Sallen-Key active filter.
Results: Summarize your results in the context of
your objectives.
A Butterworth low-pass Sallen-Key filter was
successfully designed and tested. The filter shows
a flat frequency response below the cutoff

frequency, with an average roll-off rate of -38.3
dB/decade. The filter operates within the
parameters expected of a typical Butterworth low-
pass Sallen-Key filter of the second order.
Conclusions: What can you conclude about this lab
based on your results?
Given a specifications of one filter, a person can
obtain an appropriate design by acquiring the
transfer function from the mathematical
approximation.

DEVRY ECET 350Week 2 Homework NEW
devry/ecet-350-week-2-homework-recent
Chapter 2, page 58-62, problems 2a, 2b, 2c, 7, 9a,
9b, 9c, 10a, 10b, 16a, 16b, 16c, 19, 21, 22a, 22b,
22c, 24.

DEVRY ECET 350 Week 2 iLab Signal Sampling and
Reconstruction NEW
devry/ecet-350-week-2-ilab-signal-sampling-
and-reconstruction-recent
Objectives:
• Use principles of signal sampling and
reconstruction to construct an electronic circuit to
sample, hold, and reconstruct the signal.
• Apply the antialiasing and anti-imaging filters to
perform proper simulation of signal sampling and
reconstruction.

DEVRY ECET 350 Week 3 Homework NEW
Chapter 3 Homework Problems: 3a, 3b, 3c, 5a, 5c,
5e, 7a, 9

DEVRY ECET 350 Week 3 iLab Moving Average
Digital Filters NEW
devry/ecet-350-week-3-ilab-moving-average-
digital-filters-recent
Objectives:
• Design, test, and implement antialiasing and anti-
imaging filters to be used with a real-time, digital
filtering system using a microcontroller, ADC, and
DAC.
• Implement, test, and analyze the performance of
a moving average, low-pass filter in conjunction
with the filters and real-time system from the first
objective.

Chapter 9: Finite Impulse Response Filters, pp.
314–353
Problems: 2a, 2b, 2c, 2d, 3a, 3b, 8a, 8b, 8c, 8d, 8e,
8f, 10b, 11b, 12b, 12d, 14a, 14b

DEVRY ECET 350 Week 4 iLab Low-Pass Finite
Impulse Response Filter NEW
devry/ecet-350-week-4-ilab-low-pass-finite-
impulse-response-filter-recent
Objectives: Design, implement, test, and analyze
the performance of a finite impulse response, low-
pass filter in a real-time application using the
Tower microcontroller board and ADC and DAC
interface board.

Chapter 9:
19. Design a low pass FIR filter for a 10 kHz
sampling, with a pass band edge at 2 kHz, a stop
band edge at 3 kHz, and 20 dB stop band
attenuation. Find the impulse response and the
difference equation for the filter.
26. A high pass filter with a pass band edge
frequency of 5.5 kHz must be designed for a 16
kHz sampled system. The stop band attenuation
must be at least 40 dB, and the transition width
must be no greater than 3.5 kHz. Write the
difference equation for the filter.
28. Design a band stop filter according to the
following specifications:
Pass band edges at 2 kHz and 5 kHz
Transition widths 1 kHz

Stop band attenuation ≥ 40 dB
Sampling rate 12 kHz
31. Compare the filter shape for the filter
described by the transfer function
to the shape obtained after the coefficients are
quantized.

DEVRY ECET 350 Week 5 iLab Impulse Response
Band Pass Filter NEW
devry/ecet-350-week-5-ilab-impulse-
response-band-pass-filter-recent
Objectives: Design a high-order, FIR band pass
using MATLAB and then to implement, test, and
analyze the real-time performance of that filter on
a target embedded system board. In addition,
introduce and compare the numerical formats and
processing requirements of digital filters when
implemented using floating point versus fixed
point mathematics on an embedded system.
Results: As per the requirement I designed a filter
using MatLab that would meet the required pass
band.
Conclusions: I wasn’t very happy with my results;
even though my filter passes the signal through
the pass band it didn’t seem to have very good
gain. I’m not sure what caused the loss of gain in

relation to unity, but I verified all of my equipment
and filters were working correctly.

Chapter 10 Homework Problems: 12a, 12b

DEVRY ECET 350 Week 6 iLab Infinite Impulse
Response Low-Pass Filter NEW
devry/ecet-350-week-6-ilab-infinite-impulse-
response-low-pass-filter-recent
Objectives: Design a Butterworth, low-pass filter,
and then, using a bilinear transformation
operation, create a digital IIR filter. The filter will
then be implemented and real-time performance
tested and analyzed on a target embedded system
board.
Results: Summarize your results in the context of
your objectives.
Our graph was found to be low pass for both tables
Conclusions: What can you conclude about this lab
based on your results?
As the frequency increases, the gain also goes up.

devry/ecet-350-week-7-homework-new
ECET 350
Practice Problems
1. A first-order Butterworth filter with a digital
cut-off frequency of p/4 radians is designed for a 2
kHz sampled system. The pre-warped analog
transfer function is
2. The transfer function of an analog filter is H(s) =
5000/(s + 15000). If the sampling frequency is 20
kHz, the digital filter obtained using the bilinear
transformation is
3.IIR filters are
4.Compared to FIR filters, IIR filters tend to
5.One difference between Butterworth and
Chebyshev Type I filter shapes is that
6.Bottom of Form
6.Digital convolution
7. A moving average filter

8. The gain of a filter is
9. The range of frequencies for which gain is high
is called the
10. In the stop band, a filter
11. Analog filters are often less convenient to use
than digital filters because
12. A digital filter is defined by
13. Compared to x[n], the signal x[n-2] is
14. Compared to x[n], the digital signal x[2n]
15. The notation for the function that shifts the
digital signal x[n] three steps to the left is
16. A digital signal is defined as x[n] = 5u[n-1] -
δ[n-3] + 2u[n-4]. x[3] =
17. A digital signal has the value 5 until n = 3, then
changes to zero. A function describing the signal is
18. The digital frequency of the signal x[n] =
sin(n2π/7) is
19. Which of the following statements is true?
21. If the frequency of a signal is 120 Hz and the
sampling frequency is 150 Hz, what is the aliased
frequency of the signal?
22. The purpose of an anti-aliasing filter is
23. Identify the first four images of a 300 Hz signal
sampled at 800 Hz:
24. The spectrum of a signal may be obtained from
the spectrum of its samples using

25. If a 12 kHz signal is sampled at 20 kHz
26. Increasing the order of a filter
27. For a signal with a maximum frequency of 4
kHz, what oversampling rate will leave a gap of 16
kHz between the maximum frequency of one
spectral copy and the minimum frequency of the
next?
28. An analog signal with a range of 20 V is
sampled using 10 bits. What is the size of the
quantization step?
29. The resolution of an A/D converter
30. Quantization noise is caused by
31. The dynamic range of an A/D converter is a
measure of
32. Decibels (dB) are useful because
33. SNR stands for
34. An analog signal has a range of 5 V. If the
quantization step must be no greater than 0.1 V,
how many bits must be used for A/D conversion?
35. A sample and hold circuit
36. The first step in D/A conversion is

devry/ecet-350-week-7-homework-new
ECET 350
Practice Problems
1. A first-order Butterworth filter with a digital
cut-off frequency of p/4 radians is designed for a 2
kHz sampled system. The pre-warped analog
transfer function is
2. The transfer function of an analog filter is H(s) =
5000/(s + 15000). If the sampling frequency is 20
kHz, the digital filter obtained using the bilinear
transformation is
3.IIR filters are
4.Compared to FIR filters, IIR filters tend to
5.One difference between Butterworth and
Chebyshev Type I filter shapes is that
6.Bottom of Form
6.Digital convolution
7. A moving average filter
8. The gain of a filter is

9. The range of frequencies for which gain is high
is called the
10. In the stop band, a filter
11. Analog filters are often less convenient to use
than digital filters because
12. A digital filter is defined by
13. Compared to x[n], the signal x[n-2] is
14. Compared to x[n], the digital signal x[2n]
15. The notation for the function that shifts the
digital signal x[n] three steps to the left is
16. A digital signal is defined as x[n] = 5u[n-1] -
δ[n-3] + 2u[n-4]. x[3] =
17. A digital signal has the value 5 until n = 3, then
changes to zero. A function describing the signal is
18. The digital frequency of the signal x[n] =
sin(n2π/7) is
21. If the frequency of a signal is 120 Hz and the
sampling frequency is 150 Hz, what is the aliased
frequency of the signal?
22. The purpose of an anti-aliasing filter is
23. Identify the first four images of a 300 Hz signal
sampled at 800 Hz:
24. The spectrum of a signal may be obtained from
the spectrum of its samples using
25. If a 12 kHz signal is sampled at 20 kHz

26. Increasing the order of a filter
27. For a signal with a maximum frequency of 4
kHz, what oversampling rate will leave a gap of 16
kHz between the maximum frequency of one
spectral copy and the minimum frequency of the
next?
28. An analog signal with a range of 20 V is
sampled using 10 bits. What is the size of the
quantization step?
29. The resolution of an A/D converter
30. Quantization noise is caused by
31. The dynamic range of an A/D converter is a
measure of
32. Decibels (dB) are useful because
33. SNR stands for
34. An analog signal has a range of 5 V. If the
quantization step must be no greater than 0.1 V,
how many bits must be used for A/D conversion?
35. A sample and hold circuit
36. The first step in D/A conversion is

DEVRY ECET 350 Week 7 iLab Fourier Analysis of
Time Domain Signals NEW
devry/ecet-350-week-7-ilab-fourier-analysis-
of-time-domain-signals-recent
Objective of the lab experiment:
The objective of this experiment is to perform
Fourier analysis to obtain frequency domain
signature of signals and systems that are
measured or whose characteristics are known in
time domain. Towards this end, we shall learn how
to use Fourier transform to obtain Bode plots of
systems from time domain data passing through
the system. We shall also learn the equivalence of
convolution operation in time domain with
multiplication operation in frequency domain.
Equipment list:
•Experimentally recorded time domain
characteristics of signals and systems as well as

input and output of a system, in our case a filter
(available in Doc Sharing as listed below)
•MATLAB
Software and/or other files Needed:
•Fourier_analysis_of_signals.mat:This contains
data you will need to complete this lab. It is
available in Doc Sharing.

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