Beginning Scientific Computing

Curve Fitting

Section 4.1: Classic Curve Fitting and Least-Squares Regression

Stacks Image 4052

 

[ View ]

Section 4.2: Nonlinear Regression and Gradient Descent Algorithm

Stacks Image 4043

 

[ View ]

 

 

 

 

KEY REFERENCES AND SUPPLEMENTARY VIDEOS

 

Lecture 1: Ch. 3.1

 

Stacks Image 4123

 

 
LEAST-SQUARE FITTING METHODS: The basic theory of curve fitting and least-square error is developed.

 

MATLAB COMMANDS

n/a

MATLAB CODE

 

Lecture 2: Ch. 3.2

 

Stacks Image 4104

 

 
POLYNOMIAL FITS AND SPLINES: Polynomial fitting of the data, via Lagrange polynomials, can also be considered as the fit curves go through all data points. Spline technology is developed to circumvent polynomial wiggle.

 

MATLAB COMMANDS

n/a

MATLAB CODE

 

Lecture 3: Ch. 3.3

 

Stacks Image 4076

 

 
DATA FITTING WITH MATLAB: We develop a MATLAB code that implements all the theoretical methods considered for curve fitting: least-square fits, polynomial fits and splines.

 

MATLAB COMMANDS

POLYFIT POLYVAL SPLINE INTERP1

MATLAB CODE

 

Supplementary Videos

 

Stacks Image 4097
View
Function Handles in MATLAB
Code: file.m
© 2015 kutz