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) + 03x² (1) + 04x³ (1) + 05xª (1) + 06x³ (1) + 07xº(t) Solve for the coefficients 0₁, i = 1,2,3,4,5,6,7 using batch least squares. Com- pare the result with the MATI AR function "polyfit"

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) + 03x² (1) + 04x³ (1) + 05xª (1) + 06x³ (1) + 07xº(t) Solve for the coefficients 0₁, i = 1,2,3,4,5,6,7 using batch least squares. Com- pare the result with the MATI AR function "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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