02-fft - Algorithms Lecture 2: Fast Fourier Transforms [...

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Unformatted text preview: Algorithms Lecture 2: Fast Fourier Transforms [ Fa10 ] Calvin: Heres another math problem I cant gure out. Whats 9+4? Hobbes: Ooh, thats a tricky one. You have to use calculus and imaginary numbers for this. Calvin: IMAGINARY NUMBERS?! Hobbes: You know, eleventeen, thirty-twelve, and all those. Its a little confusing at rst. Calvin: How did YOU learn all this? Youve never even gone to school! Hobbes: Instinct. Tigers are born with it. Calvin and Hobbes (January 6, 1998) It needs evaluation So let the games begin A heinous crime, a show of force A murder would be nice, of course Bad Horses Letter, Dr. Horribles Sing-Along Blog (2008) 2 Fast Fourier Transforms ? 2.1 Polynomials In this lecture well talk about algorithms for manipulating polynomials : functions of one variable built from additions subtractions, and multiplications (but no divisions). The most common representation for a polynomial p ( x ) is as a sum of weighted powers of a variable x : p ( x ) = n X j = a j x j . The numbers a j are called coefcients . The degree of the polynomial is the largest power of x ; in the example above, the degree is n . Any polynomial of degree n can be specied by a sequence of n + 1 coefcients. Some of these coefcients may be zero, but not the n th coefcient, because otherwise the degree would be less than n . Here are three of the most common operations that are performed with polynomials: Evaluate: Give a polynomial p and a number x , compute the number p ( x ) . Add: Give two polynomials p and q , compute a polynomial r = p + q , so that r ( x ) = p ( x )+ q ( x ) for all x . If p and q both have degree n , then their sum p + q also has degree n . Multiply: Give two polynomials p and q , compute a polynomial r = p q , so that r ( x ) = p ( x ) q ( x ) for all x . If p and q both have degree n , then their product p q has degree 2 n . Suppose we represent a polynomial of degree n as an array of n + 1 coefcients P [ 0.. n ] , where P [ j ] is the coefcient of the x j term. We learned simple algorithms for all three of these operations in high-school algebra: E VALUATE ( P [ 0.. n ] , x ) : X 1 X = x j y for j 0 to n y y + P [ j ] X X X x return y A DD ( P [ 0.. n ] , Q [ 0.. n ]) : for j 0 to n R [ j ] P [ j ]+ Q [ j ] return R [ 0.. n ] M ULTIPLY ( P [ 0.. n ] , Q [ 0.. m ]) : for j 0 to n + m R [ j ] for j 0 to n for k 0 to m R [ j + k ] R [ j + k ]+ P [ j ] Q [ k ] return R [ 0.. n + m ] c Copyright 2010 Jeff Erickson. Released under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License ( http://creativecommons.org/licenses/by-nc-sa/3.0/ ). Free distribution is strongly encouraged; commercial distribution is expressly forbidden. See http://www.cs.uiuc.edu/~jeffe/teaching/algorithms/ for the most recent revision. 1 Algorithms Lecture 2: Fast Fourier Transforms [ Fa10 ] E VALUATE uses O ( n ) arithmetic operations....
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This note was uploaded on 10/14/2011 for the course ECON 101 taught by Professor Smith during the Spring '11 term at West Virginia University Institute of Technology.

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02-fft - Algorithms Lecture 2: Fast Fourier Transforms [...

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