Category Archives: ECET 350

ECET 350 Week 7 iLab Fourier Analysis of Time Domain Signals NEW

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ECET 350  Week 7 iLab Fourier Analysis of Time Domain Signals NEW

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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ECET 350 Week 7 Homework NEW

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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?
20. 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 

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ECET 350 Week 6 iLab Infinite Impulse Response Low-Pass Filter NEW

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ECET 350  Week 6 iLab Infinite Impulse Response Low-Pass Filter NEW

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.

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ECET 350 Week 5 iLab Impulse Response Band Pass Filter NEW

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ECET 350  Week 5 iLab Impulse Response Band Pass Filter NEW

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.

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ECET 350 Week 5 Homework NEW

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ECET 350  Week 5 Homework NEW

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.

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ECET 350 Week 4 iLab Low-Pass Finite Impulse Response Filter NEW

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ECET 350  Week 4 iLab Low-Pass Finite Impulse Response Filter NEW

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.

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ECET 350 Week 3 iLab Moving Average Digital Filters NEW

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ECET 350  Week 3 iLab Moving Average Digital Filters NEW

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.

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ECET 350 Week 2 iLab Signal Sampling and Reconstruction NEW

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ECET 350  Week 2 iLab Signal Sampling and Reconstruction NEW

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.

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