Computer Programming: Polynomials, Curve fitting ... · Curve-fitting • Curve fitting, also...

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Computer Programming: Polynomials, Curve fitting, Interpolation Asst. Prof. Dr. Yalçın İşler Izmir Katip Celebi University

Transcript of Computer Programming: Polynomials, Curve fitting ... · Curve-fitting • Curve fitting, also...

Page 1: Computer Programming: Polynomials, Curve fitting ... · Curve-fitting • Curve fitting, also called regression analysis, is a process of fitting a function to a set of data points.

Computer Programming: Polynomials, Curve fitting,

Interpolation

Asst. Prof. Dr. Yalçın İşler

Izmir Katip Celebi University

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Outline

• Polynomials

• Curve-fitting

• Interpolation

• Basic fitting interface

• Examples

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Polynomials

• Polynomials are mathematical expressions that are frequently used for problem solving and modeling in science and engineering.

• Polynomials are functions that have the form:

• The coefficients «a» are real numbers and n is a nonnegative integer, is the degree, or order, of the polynomial.

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Polynomials (cont’d)

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Value of Polinomial

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Roots of Poliynomial

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Roots (cont’d)

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Polynomial Arithmetics

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Polynomial Arithmetics (cont’d)

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Polynomial Arithmetics (cont’d)

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Polynomial Derivatives

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Polynomial Derivatives (cont’d)

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Curve-fitting

• Curve fitting, also called regression analysis, is a process of fitting a function to a set of data points. The function can then be used as a mathematical model of the data. Since there are many types of functions (linear, polynomial, power, exponential, etc.) curve fitting can be a complicated process. Many times there is some idea of the type of function that might fit the given data and the need is only to determine the coefficients of the function.

• In other situations, where nothing is known about the data, it is possible to make different types of plots which provide information about possible forms of functions that might give a good fit to the data.

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polyfit

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polyfit for other function types

After plotting the sample values, you can decide the suitable form of the polyfit function.

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Interpolation

• Interpolation is estimation of values between data points.

• In onedimensional interpolation each point has one independent variable (x) and one dependent variable (y).

• In two-dimensional interpolation each point has two independent variables (x and y) and one dependent variable (z).

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1D Interpolation

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1D Interpolation (cont’d)

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Basic fitting interface • To activate the basic fitting interface, the user first has

to make a plot of the data points. Then, the interface is activated by selecting Basic Fitting in the Tools menu. This opens the Basic Fitting Window.

Several fits can be selected and displayed simultaneously.

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Basic fitting interface (cont’d)

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Laboratory Session

Do both examples and sample applications in Chapter 8 of the textbook.

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Homework #10

Not later than the next week:

Solve problems 2, 10, 15, and 18 from the Chapter 8 of the textbook using Matlab.