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Generating function

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The idea behind generating functions is to create a power series whose coefficients, , give the terms of a sequence which of interest. Therefore the power series (i.e. the generating function) is and the sequence is .

Contents

Simple Example

If we let , then we have {n \choose 0}+{n \choose 1}x + {n \choose 2}x^2+\cdots+.

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

The reason to go to such lengths is that our above polynomial is equal to (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 ), also {n \choose 1}+{n \choose 3}+\cdots={n \choose 0}+{n \choose 2}+\cdots.

Convolutions

Suppose we have the sequences and . We can create a new sequence, called the convolution of and , 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 is the generating function for and is the generating function for , then the generating function for is .

See also

External Link

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