Gen ate sets of information (xi, Yi) utilizing = (0 : 0.1 : 2.5)';y=erf(x); in MATLAB. Expect that the result y(t) can be approximated by a 6th - th degree polynomial as far as x(t) (counting a consistent predisposition term, so seven dad rameters altogether): _y(t) = 0₁ + 0₂x(1) + 03x² (1) + 04x³ (1) + 05xª (1) + 0x³ (1) + 07xº (1) Settle for the coefficients 0₁, I = 1,2,3,4,5,6,7 utilizing clump least squares. Com-pare the outcome w. ith the MATLAR capability "polyfit."
Gen ate sets of information (xi, Yi) utilizing = (0 : 0.1 : 2.5)';y=erf(x); in MATLAB. Expect that the result y(t) can be approximated by a 6th - th degree polynomial as far as x(t) (counting a consistent predisposition term, so seven dad rameters altogether): _y(t) = 0₁ + 0₂x(1) + 03x² (1) + 04x³ (1) + 05xª (1) + 0x³ (1) + 07xº (1) Settle for the coefficients 0₁, I = 1,2,3,4,5,6,7 utilizing clump least squares. Com-pare the outcome w. ith the MATLAR capability "polyfit."
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Gen ate sets of information (xi, Yi) utilizing = (0 : 0.1 : 2.5)';y=erf(x); in MATLAB. Expect that the result y(t) can be approximated by a 6th - th degree polynomial as far as x(t) (counting a consistent predisposition term, so seven dad rameters altogether): _y(t) = 0₁ + 0₂x(1) + 03x² (1) + 04x³ (1) + 05xª (1) + 0x³ (1) + 07xº (1) Settle for the coefficients 0₁, I = 1,2,3,4,5,6,7 utilizing clump least squares. Com-pare the outcome w.
ith the MATLAR capability "polyfit."
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