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Generating function

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The idea behind generating functions is to create a power series whose coefficients, c_0, c_1, c_2, \ldots, give the terms of a sequence which of interest. Therefore the power series (i.e. the generating function) is c_0 + c_1 x + c_2 x^2 + \cdots and the sequence is c_0, c_1, c_2,\ldots.

Contents

Simple Example

If we let A(k)={n \choose k}, then we have {n \choose 0}+{n \choose 1}x + {n \choose 2}x^2+\cdots+{n \choose n}x^n.

This function can be described as the number of ways we can get {k} heads when flipping n different coins.

The reason to go to such lengths is that our above polynomial is equal to (1+x)^n (which is clearly seen due to the Binomial Theorem). By using this equation, we can rapidly uncover identities such as {n \choose 0}+{n \choose 1}+...+{n \choose n}=2^n(let {x}=1), also {n \choose 1}+{n \choose 3}+\cdots={n \choose 0}+{n \choose 2}+\cdots.

Convolutions

Suppose we have the sequences a_0, a_1, a_2, ... and b_0, b_1, b_2, .... We can create a new sequence, called the convolution of a and b, defined by c_n = a_0b_n + a_1b_{n-1} + ... + a_nb_0. Generating functions allow us to represent the convolution of two sequences as the product of two power series. If A is the generating function for a and B is the generating function for b, then the generating function for c is AB.

See also

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