Lagrange interpolation formula

In summary, the conversation discusses how to find polynomial functions of degree n-1 that have specific values at given points. The first part (a) involves finding a polynomial f_i that is equal to 1 at x_i and 0 at all other distinct numbers x_j. The hint explains that this can be achieved by taking the product of all (x-x_j) for j≠i, which is equal to 0 at x_j if j≠i. The second part (b) introduces the Lagrange interpolation formula, which uses the functions f_i from part (a) to find a polynomial f of degree n-1 with given values at x_i. The conversation also mentions that the formula is sometimes called the B
  • #1
swevener
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Homework Statement


(a) If [itex]x_{1},\ldots, x_{n}[/itex] are distinct numbers, find a polynomial function [itex]f_{i}[/itex] of degree [itex]n - 1[/itex] which is 1 at [itex]x_{i}[/itex] and 0 at [itex]x_{j}[/itex] for [itex]j \ne i[/itex]. Hint: the product of all [itex](x - x_{j})[/itex] for [itex]j \ne i[/itex] is 0 at [itex]x_{j}[/itex] if [itex]j \ne i[/itex]. This product is usually denoted by
[tex]\prod_{\substack{j = 1 \\ j \ne i}}^{n} (x - x_{j}).[/tex]
(b) Now find a polynomial function [itex]f[/itex] of degree [itex]n - 1[/itex] such that [itex]f(x_{i}) = a_{i}[/itex], where [itex]a_{1},\ldots,a_{n}[/itex] are given numbers. (You should use the functions [itex]f_{i}[/itex] from part (a). The formula you will obtain is called the "Lagrange interpolation formula.")

3. [strike]The attempt at a solution[/strike] Questions
Why are these polynomials of degree [itex]n - 1[/itex]? Because of the [itex]j \ne i[/itex]?
[strike]And the hint in part (a), where does that come from? Why can we say the product is zero if[/strike] [itex]j \ne i[/itex]? Figured this one out. I misread the problem.
 
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  • #2
Anyone has a MATLAB code for lagrange interpolation and Barycentric , please help
 

Related to Lagrange interpolation formula

1. What is Lagrange interpolation formula?

The Lagrange interpolation formula is a mathematical method used to approximate a function given a set of data points. It involves fitting a polynomial curve to the data points, which can then be used to estimate values for the function at other points.

2. How does the Lagrange interpolation formula work?

The formula works by constructing a polynomial of degree n-1, where n is the number of data points. This polynomial passes through all of the data points and can be used to interpolate values for the function at any point within the range of the data.

3. When is the Lagrange interpolation formula used?

The formula is used when a function is known only at a few data points, but values for the function are needed at other points within the range of the data. It is commonly used in numerical analysis and scientific computing.

4. What are the advantages of using the Lagrange interpolation formula?

One advantage is that the formula is simple and easy to use, requiring only basic algebraic operations. It also produces a smooth curve that passes through all the data points, unlike other interpolation methods that may produce jagged curves. Additionally, the formula can be extended to higher dimensions for multivariate interpolation problems.

5. Are there any limitations to the Lagrange interpolation formula?

Yes, the formula can produce inaccurate results if the data points are too widely spaced or if the degree of the polynomial is too high. It can also be computationally expensive for a large number of data points. In these cases, other interpolation methods such as spline interpolation may be more suitable.

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