Difference between revisions of "Spring 2020 Assignment 8"

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==Circuit analogies==
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For each of the systems below, find an analogous circuit.
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File:Thermal System Analogy Problem.png |Thermal system:Coffee in a thermos
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File:Mechanical System Analogy Problem.png|Mechanical system: mass and damper
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==Convolution practice==
 
==Convolution practice==
 
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==Circuit analogies==
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==Fourier transform table==
For each of the systems below, find an analogous circuit.
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The two tables below show important properties of the Fourier transform and several useful transform pairs. You can use the tables of pairs and properties to figure out the transforms of an endless number of functions.
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[[Image: FourierTransformsTable.png|thumb|left|500 px|<caption>Short table of Fourier transform properties</caption>]]
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[[Image: TimeFrequencyDomains_MoreTransformPairsTable.png|thumb|left|500 px|<caption>Short table of Fourier transform pairs</caption>]]
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<li>Sketch each function in table of transform pairs as well as the magnitude of its Fourier transform. Show relevant constants (for example: ''a'', <math>\alpha</math>, and <math>f_0</math>).</li>
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<li>Sketch the transform of <math>\cos^4(\omega_0 t)</math>.</li>
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<li>Sketch the fourier transform of <math>e^{-\alpha t} u(t) \times \cos(\omega_0 t)</math>. Assume <math>\alpha\ll\omega_0</math>.</li>
 
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The table below shows plots of eight time-domain signals A-H. The table on the right includes magnitude plots of the Fourier transform of ten signals numbered 1-10. Some of the frequency plots are shown on log-log axes and some are linear, as indicated by the plot title.
File:Thermal System Analogy Problem.png |Thermal system:Coffee in a thermos
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File:Mechanical System Analogy Problem.png|Mechanical system: mass and damper
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[[Image: PSet4_ConvolutionImage.png|thumb|center|500 px|<caption>Table 8.0.3</caption>]]
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{{:Assignment 8, Part 0: convolution practice}}
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For each time domain signal A-H, write the number 1-10 in the empty column of the matching frequency-domain signal. You may use a numbered plot more than once.
  
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''Hint:'' Gaussian or white noise is a random signal with equal contributions from ''every frequency''.}}  
 
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Revision as of 03:10, 23 April 2020

20.309: Biological Instrumentation and Measurement

ImageBar 774.jpg

Circuit analogies


Pencil.png

For each of the systems below, find an analogous circuit.


Convolution practice


Pencil.png

For each of the pairs of functions below, plot the convolution of the two functions, $ Y=A*B $


A B Y
Delta(t+1)+delta(t-1).png Delta(t+1)+delta(t-1).png Bare convolution axes.png
Delta(t+1)+delta(t-1).png Box w=1.png] Bare convolution axes.png
Delta(t+1)+delta(t-1).png Box w=2.png Bare convolution axes.png
Box w=1.png Box w=1.png Bare convolution axes.png
Delta(t+1)+delta(t-1).png Triangle.png Bare convolution axes.png
Delta(t).png Triangle.png Bare convolution axes.png


Fourier transform table

The two tables below show important properties of the Fourier transform and several useful transform pairs. You can use the tables of pairs and properties to figure out the transforms of an endless number of functions.

Short table of Fourier transform properties
Short table of Fourier transform pairs


Pencil.png
  1. Sketch each function in table of transform pairs as well as the magnitude of its Fourier transform. Show relevant constants (for example: a, $ \alpha $, and $ f_0 $).
  2. Sketch the transform of $ \cos^4(\omega_0 t) $.
  3. Sketch the fourier transform of $ e^{-\alpha t} u(t) \times \cos(\omega_0 t) $. Assume $ \alpha\ll\omega_0 $.
  4. </div>


The table below shows plots of eight time-domain signals A-H. The table on the right includes magnitude plots of the Fourier transform of ten signals numbered 1-10. Some of the frequency plots are shown on log-log axes and some are linear, as indicated by the plot title.

Table 8.0.3


Pencil.png

For each time domain signal A-H, write the number 1-10 in the empty column of the matching frequency-domain signal. You may use a numbered plot more than once.

Hint: Gaussian or white noise is a random signal with equal contributions from every frequency.


</div>
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