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Exponential generating functions
If we had wanted to be absolutely precise earlier in the chapter, we would have referred to the generating functions we studied as ordinary generating functions or even ordinary power series generating functions.
Exponential generating functions
If we had wanted to be absolutely precise earlier in the chapter, we would have referred to the generating functions we studied as ordinary generating functions or even ordinary power series generating functions. This is because there are other types of generating functions, based on other types of power series. In this section, we briefly introduce another type of generating function, the exponential generating function. While an ordinary generating function has the form \(\sum_{n} a_n x^n\), an exponential generating function is based on the power series for the exponential function \(e^x\). Thus, the exponential generating function for the sequence \(\{a_n\colon n\geq 0\}\) is \(\sum_n a_n x^n/n!\). In this section, we will see some ways we can use exponential generating functions to solve problems that we could not tackle with ordinary generating functions. However, we will only scratch the surface of the potential of this type of generating function. We begin with the most fundamental exponential generating function, in analogy with the ordinary generating function \(1/(1-x)\) of .
Example
Consider the constant sequence \(1, 1, 1, 1, \dots\). Then the exponential generating function for this sequence is \[\begin{aligned}\end{aligned}\] From calculus, you probably recall that this is the power series for the exponential function \(e^x\), which is why we call this type of generating function an exponential generating function. From this example, we can quickly recognize that the exponential generating function for the number of binary strings of length \(n\) is \(e^{2x}\) since \[\begin{aligned}\end{aligned}\]
In our study of ordinary generating functions earlier in this chapter, we considered examples where quantity (number of apples, ) mattered but order did not. One of the areas where exponential generating functions are preferable to ordinary generating functions is in applications where order matters, such as counting strings. For instance, although the bit strings \(10001\) and \(011000\) both contain three zeros and two ones, they are not the same strings. On the other hand, two fruit baskets containing two apples and three oranges would be considered equivalent, regardless of how you arranged the fruit. We now consider a couple of examples to illustrate this technique.
We can also use exponential generating functions when there are bounds on the number of times a symbol appears, such as in the following example.
Condensed: the full section is in Keller & Trotter, Applied Combinatorics.
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연습 (1)
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Suppose Alice's mobile phone passcode restrictions in were modified so that the number of \(3\)s had to be at least two. Then one of the factors of \(e^x\) in the generating function would have to be replaced by what? You can express your answer as either a series or in terms of \(e^x\) with suitable adjustments.
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사람들이 묻는 질문
Permutation or combination?
Ask whether order matters. A lock code is a permutation (order matters); a hand of cards is a combination (it does not).
What is a graph in this sense?
Dots (vertices) joined by lines (edges), not a plot. Road maps, social networks and molecules are graphs; questions like "is there a route" and "how few colours" are graph theory.
이 페이지의 일부는 다음에서 변경되었습니다. Keller & Trotter, Applied Combinatorics (CC BY-SA 4.0). 여기서 압축하고 다시 설명; 오류는 우리의.
에 더 Combinatorics & Graph Theory
The counting principlesPigeonhole principle and inclusion, exclusionBinomial coefficients and Pascal's triangleRecurrences and generating functionsGraphs: vertices, edges, degreesPaths, cycles, trees, Euler and HamiltonColouring and planar graphs