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Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN: 9780133594140
Author: James Kurose, Keith Ross
Publisher: PEARSON
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
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

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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