Polynomial Interpolation: Difference between revisions

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[[File:Polynomial Interpolation - Space.png|1000px]]
[[File:Polynomial Interpolation - Space.png|1000px]]


== Pareto Frontier Improvements Graph ==  
== Time-Space Tradeoff ==  


[[File:Polynomial Interpolation - Pareto Frontier.png|1000px]]
[[File:Polynomial Interpolation - Pareto Frontier.png|1000px]]

Revision as of 14:48, 15 February 2023

Description

Given a finite number of points $x_1, \ldots , x_n$, some real constants $y_1, \ldots , y_n$ and a subspace $V$ of $\Pi^d$, find a polynomial $p \in V$, such that

$p(x_j) = y_j$, $j = 1, ... , n$

Parameters

n: number of points

d: dimension of space

Table of Algorithms

Name Year Time Space Approximation Factor Model Reference
Gaussian elimination -150 $O(n^{3})$ $O(n^{2})$ Exact Deterministic
Bjorck 1970 $O(n^{2})$ $O(n)$ Exact Deterministic Time & Space
Higham 1988 $O(n^{2})$ $O(n)$ Exact Deterministic Time & Space
Calvetti, Reichel 1993 $O(n^{2})$ $O(n)$? Exact Deterministic Time

Time Complexity Graph

Polynomial Interpolation - Time.png

Space Complexity Graph

Polynomial Interpolation - Space.png

Time-Space Tradeoff

Polynomial Interpolation - Pareto Frontier.png