Elements Of Electromagnetics
Elements Of Electromagnetics
7th Edition
ISBN: 9780190698614
Author: Sadiku, Matthew N. O.
Publisher: Oxford University Press
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Problem 1/MatlabGrader (20 points) (Core Course Outcome 4)
Develop a Matlab function myFitExam that finds the best fit of the function
p(t) = as
sin³ (t) + b sin² (t) + csin(t) + d
(1)
to a given set of data points (ti, pi) using regression. Here t is in radians.
The function input shall be
⚫t: column vector of data values t
⚫ p: column vector of data values p
The function output shall be
• a: scalar containing the best fit coefficient a
b: scalar containing the best fit coefficient b
c: scalar containing the best fit coefficient c
d: scalar containing the best fit coefficient d
In the function use only functions developed in this class in modules 1 - 4. You do not need to provide these functions in your
submission. They will be provided when assessing your function after the deadline.
Note: no assessments will be performed on your submitted function before the exam deadline. Scores on Canvas for this problem
before the exam has been fully graded are meaningless.
Required submission:
☐ well commented function source code submitted to Matlab Grader using the Canvas link for Exam 4 - Problem 1
Problem 2 (15 points) (Core Course Outcome 4)
Consider the following unsorted table of measured data points (ti, pi):
t 1/4 1 6 5
2
1/2
7/2
р 1/2 1 1
-1
3/2 1
-2/3
Use your function myFit Exam from problem 1 to determine the coefficients a, b, c, and d in p(t), see Eq. (1), that best fit the data.
Print the coefficients with at least 7 significant digitis.
Required submission:
☐ printout of script source code used to solve this problem in your Gradescope submission;
printout of coefficients with at least 7 significant digits in your Gradescope submission;
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Transcribed Image Text:Problem 1/MatlabGrader (20 points) (Core Course Outcome 4) Develop a Matlab function myFitExam that finds the best fit of the function p(t) = as sin³ (t) + b sin² (t) + csin(t) + d (1) to a given set of data points (ti, pi) using regression. Here t is in radians. The function input shall be ⚫t: column vector of data values t ⚫ p: column vector of data values p The function output shall be • a: scalar containing the best fit coefficient a b: scalar containing the best fit coefficient b c: scalar containing the best fit coefficient c d: scalar containing the best fit coefficient d In the function use only functions developed in this class in modules 1 - 4. You do not need to provide these functions in your submission. They will be provided when assessing your function after the deadline. Note: no assessments will be performed on your submitted function before the exam deadline. Scores on Canvas for this problem before the exam has been fully graded are meaningless. Required submission: ☐ well commented function source code submitted to Matlab Grader using the Canvas link for Exam 4 - Problem 1 Problem 2 (15 points) (Core Course Outcome 4) Consider the following unsorted table of measured data points (ti, pi): t 1/4 1 6 5 2 1/2 7/2 р 1/2 1 1 -1 3/2 1 -2/3 Use your function myFit Exam from problem 1 to determine the coefficients a, b, c, and d in p(t), see Eq. (1), that best fit the data. Print the coefficients with at least 7 significant digitis. Required submission: ☐ printout of script source code used to solve this problem in your Gradescope submission; printout of coefficients with at least 7 significant digits in your Gradescope submission;
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