Interpolation with 2 variables

In summary, given three points, a polynomial function can be found that intersects those points. This can be extended to more points, where a relationship exists between the coefficients of a quadratic equation and the coordinates of the points. This is a standard result and can be found by solving a linear system. However, the equation for finding the coefficients in terms of the points' coordinates is not provided in the Wikipedia page.
  • #1
Jhenrique
685
4
If given three points ##P_0 = (x_0, y_0)##, ##P_1 = (x_1, y_1)## and ##P_2 = (x_2, y_2)##, the polynomial function ##f(x)## that intersect those points is ##f(x) = a_2 x^2 + a_1 x^1 + a_0 x^0##.

where:
##
\begin{bmatrix}
a_0\\
a_1\\
a_2\\
\end{bmatrix}
=

\begin{bmatrix}
x_0^0 & x_1^0 & x_2^0 \\
x_0^1 & x_1^1 & x_2^1 \\
x_0^2 & x_1^2 & x_2^2 \\
\end{bmatrix}^{-T}

\begin{bmatrix}
y_0\\
y_1\\
y_2\\
\end{bmatrix}##

And this ideia can extended for ##P_n## points... so, analogously, given a set of points, exist a relationship between the coefficients of ##Ax^2+Bxy+Cy^2+Dx+Ey+F=0## and the coordinates of the points?
 
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  • #2
Yes, that is a standard result. Five points in the plane determine a quadratic in two variables, if no three are collinear the quadratic will be unique and non degenerate. The coefficients can be found by solving a linear system like in the one variable case.

http://en.wikipedia.org/wiki/Five_points_determine_a_conic
 
  • #3
lurflurf said:
Yes, that is a standard result. Five points in the plane determine a quadratic in two variables, if no three are collinear the quadratic will be unique and non degenerate. The coefficients can be found by solving a linear system like in the one variable case.

http://en.wikipedia.org/wiki/Five_points_determine_a_conic

Yeah! But don't exist the equation of the coefficients in function of the points' coordinates in the wikipage...
 
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FAQ: Interpolation with 2 variables

What is interpolation with 2 variables?

Interpolation with 2 variables is a mathematical method used to estimate the value of a function at a point that lies between two known data points. It involves using a set of data points with two independent variables and finding the corresponding value of the dependent variable at a specific point.

How is interpolation with 2 variables different from interpolation with 1 variable?

Interpolation with 1 variable involves estimating the value of a function at a point using a set of data points with only one independent variable. Interpolation with 2 variables, on the other hand, uses a set of data points with two independent variables to estimate the value of a function at a specific point. This allows for a more accurate estimation.

What are the applications of interpolation with 2 variables?

Interpolation with 2 variables has various applications in fields such as physics, engineering, and computer graphics. It is commonly used in data analysis and prediction, image and signal processing, and curve fitting. It is also used in creating maps and charts based on geographical data.

What are the different methods of interpolation with 2 variables?

There are several methods of interpolation with 2 variables, including bilinear interpolation, bicubic interpolation, and spline interpolation. These methods differ in the way they use the data points to estimate the value of a function at a point. Bilinear interpolation, for example, uses a weighted average of the four nearest data points, while bicubic interpolation uses a weighted average of 16 surrounding data points.

What are the limitations of interpolation with 2 variables?

Interpolation with 2 variables can produce accurate results, but it is limited by the quality and quantity of the data points. The data points must be evenly spaced and cover a significant range of the function's values for the estimation to be reliable. Additionally, interpolation cannot accurately estimate values outside of the range of the data points, and it may not work well with irregularly spaced data points.

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