Curve Fitting You have 3 points (1, 6), (2, 4), and (4, 3). Find the best function to fit these data from the followingfunctions:(1) y = a₁ + a₁x(2) y = Ae Bx(3) y = A + B ¹²Hint:1-Data Linearization MethodV = a₁ + a₁UΣ=10i[Σk ² = 1 Ui vi]Root mean-square error functionRoot mean-square error function e(f) is defined by:€ (ƒ) = [ Σ*²=₁[Y(x^,) — y₁]²] ¹/²Σ=1uikk[ Σ ² = ₁ U₂₁ [²²_₁ U ₁ ² ][]B. Power Fit Methoda ==Li=1Σ1 xi¹¹ yiΣ=1x;2n

Given points:Given functions:1) 2) 3) To find:The function which is best fit on each models.

You have 3 points (1, 6), (2, 4), and (4, 3). Find the best function to fit these data from the following functions: (1) y = a₁ + a₁x (2) y = AeBx (3) y = A + B ² Hint: 1-Data Linearization Method V = a₁ + a₂U k Σ=1ui rk k [Σ14: _Σημε[@] = Σ=10; k ¹2i=1 U₁ V₁]

You have 3 points (1, 6), (2, 4), and (4, 3). Find the best function to fit these data from the following functions: (1) y = a₁ + a₁x (2) y = AeBx (3) y = A + B ² Hint: 1-Data Linearization Method V = a₁ + a₂U k Σ=1ui rk k [Σ14: _Σημε[@] = Σ=10; k ¹2i=1 U₁ V₁]

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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