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Problem 1 Generate pairs of data (x;, yi) using = (0:0.1: 2.5)';y= erf(x); in MATLAB. Assume that the output y(t) can be approximated by a sixth – th degree polynomial in terms of x(t) (including a constant bias term, so seven pa- rameters in total): y(t) = 01 + 0,x(t) + 03x (t) + 04x°(t) + 05x*(t) + O6x* (t) + 0,x° (t) Solve for the coefficients 0;, i = 1,2,3,4,5,6,7 using batch least squares. Com- pare the result with the MATLAB function "polyfit."

Problem 1 Generate pairs of data (x;, yi) using = (0:0.1: 2.5)';y= erf(x); in MATLAB. Assume that the output y(t) can be approximated by a sixth – th degree polynomial in terms of x(t) (including a constant bias term, so seven pa- rameters in total): y(t) = 01 + 0,x(t) + 03x (t) + 04x°(t) + 05x*(t) + O6x* (t) + 0,x° (t) Solve for the coefficients 0;, i = 1,2,3,4,5,6,7 using batch least squares. Com- pare the result with the MATLAB function "polyfit."

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Problem 1 Generate pairs of data (x;, yi) using x= (0:0.1: 2.5)';y= erf(x); in MATLAB. Assume that the output y(t) can be approximated by a sixth – th degree polynomial in terms of x(t) (including a constant bias term, so seven pa- rameters in total): y(t) = 01 + 02x(t) + O3x² (t) + O4x*(t) + 0sx* (t) + O6x*(t) +0,x°(t) Solve for the coefficients 0;, i = 1,2,3,4,5,6,7 using batch least squares. Com- pare the result with the MATLAB function "polyfit." %3D
Transcribed Image Text:Problem 1 Generate pairs of data (x;, yi) using x= (0:0.1: 2.5)';y= erf(x); in MATLAB. Assume that the output y(t) can be approximated by a sixth – th degree polynomial in terms of x(t) (including a constant bias term, so seven pa- rameters in total): y(t) = 01 + 02x(t) + O3x² (t) + O4x*(t) + 0sx* (t) + O6x*(t) +0,x°(t) Solve for the coefficients 0;, i = 1,2,3,4,5,6,7 using batch least squares. Com- pare the result with the MATLAB function "polyfit." %3D
Problem 2 Write MATLAB code to solve Problem 1 using the least-squares gradient method with O(0) = 0 and I= 301. Plot 0;(t) versus t. Compare the result with that in Problem 1. Note that the Euler method for the least-squares gradient method is expressed as O; - ATO (x;) 4" (x;) O; – Oit! Yi %3D
Transcribed Image Text:Problem 2 Write MATLAB code to solve Problem 1 using the least-squares gradient method with O(0) = 0 and I= 301. Plot 0;(t) versus t. Compare the result with that in Problem 1. Note that the Euler method for the least-squares gradient method is expressed as O; - ATO (x;) 4" (x;) O; – Oit! Yi %3D
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