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Let \(\Sigma=\\{0,1,2,3\\}\). For \(n \geq 1\), let \(a_{n}\) count the number of strings in \(\Sigma^{n}\) containing an odd number of 1 's. Find and solve a recurrence relation for \(a_{n}\).

Short Answer

Expert verified
The recurrence relation is \(a_n = 4^{n-1} - a_{n-1}\), and the base case is \(a_1=1\).

Step by step solution

01

Identify the Strings of Length 1

First, we need to find the strings of length 1 that contain an odd number of 1's. In this case, the only string that fits this definition is '1'. Hence, \(a_1=1\).
02

Determine the Number of Strings of Length \(n\)

Next, we calculate the total number of strings of length \(n\), which is \(4^n\) since there are 4 possible alphabet values for each character in the string.
03

Determine the Number of Strings with an Even Number of 1's

Now, let's denote by \(b_n\) the number of strings of length \(n\) which contain an even number of 1's. It's clear that the sum \(a_n + b_n\) is \(4^n\) as it includes all possible strings of length \(n\). However, looking at the strings of length \(n-1\), we have \(a_{n-1} + b_{n-1} = 4^{n-1}\). For each string of length \(n-1\), we can add '0', '2', or '3' at the end to get a string of length \(n\) with the same number of 1's, and we can add '1' to get a string of length \(n\) with the number of 1's increased by one. Therefore, we have \(4^{n-1} = a_{n-1} + b_{n-1} = b_n + a_n\). By comparing this equation with \(a_n + b_n = 4^n\), we can find the recurrence relation.
04

Form the Recurrence Relation

From the above, by comparing \(b_n+ a_n = 4^n\) with \(b_n + a_n = 4^{n-1}\), we can easily get the equation \(a_n = 4^{n-1} - a_{n-1}\). This is the recurrence relation for \(a_n\).

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Understanding Strings
Strings are sequences of characters. In our exercise, the set \(\Sigma = \{0, 1, 2, 3\}\) represents the alphabet from which these characters are drawn. An important aspect of strings is their length, denoted as \(n\) in this context, which tells us how many characters are in the string.
For example, a string of length 3 could be '012' or '333'.

In counting problems like this one, we're often interested in strings that meet certain criteria. Here, we're concerned with strings that contain an **odd number of 1's.**
  • The total number of possible strings of length \(n\) is calculated by raising the size of \(\Sigma\) (which is 4) to the power of \(n\), resulting in \(4^n\).
  • Understanding this total helps us form parts of a recurrence relation since any string of a given length can be broken down into smaller problems.
Recurrence Relation for Sequences
A recurrence relation is a mathematical way to define a sequence of numbers, specifying each term as a function of the preceding ones.
In this problem, we are interested in the sequence \(a_n\), which counts the number of strings of length \(n\) with an odd number of 1's.

By looking at the progression from previous steps, we need to find a way to relate \(a_{n}\) with \(a_{n-1}\).
  • We start with the base case where \(a_1 = 1\). This is because only the string '1' from \(\Sigma^{1}\) meets the condition.
  • To move forward, we consider strings of length \(n\) and relate them to those of length \(n-1\).
  • The key transformation is recognizing that the relation \(a_n = 4^{n-1} - a_{n-1}\) accurately depicts this progression.
This relation makes it possible to compute \(a_n\) using the previously calculated \(a_{n-1}\), providing an efficient way to build larger terms from smaller ones.
Counting Strings with Conditions
Counting strings with conditions involves identifying strings that meet specific criteria, like containing an odd number of a certain character—in this case, '1'.
We break this down by understanding how each addition to a string affects its character count.

Consider a string of length \(n-1\).
  • If we add '1', it changes the parity of the number of 1's (odd becomes even, and vice versa).
  • If we add '0', '2', or '3', the parity remains the same.
This insight is crucial because it leads to the understanding that we can split all strings into two categories: those with an odd number of 1's and those with an even number of 1's.

Hence, we can deduce:
- For every odd string of length \(n-1\), we form an even string of length \(n\) by adding '1'.
- Conversely, for every even string of length \(n-1\), adding '1' creates an odd string.
This balanced approach ensures that our recurrence relation \(a_n = 4^{n-1} - a_{n-1}\) correctly accounts for the entirety of \(\Sigma^n\), linking back to how many strings meet our condition of having an odd number of 1's.

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Most popular questions from this chapter

If \(a_{n}, n \geq 0\), is the unique solution of the recurrence relation \(a_{n+1}-d a_{n}=0\), and \(a_{3}=153 / 49, a_{5}=1377 / 2401\), what is \(d ?\)

Renu wants to sell her laptop for \(\$ 4000\). Narmada offers to buy it for \(\$ 3000\). Renu then splits the difference and asks for \(\$ 3500\). Narmada likewise splits the difference and makes a new offer of \(\$ 3250\). (a) If the women continue this process (of asking prices and counteroffers), what will Narmada be willing to pay on her 5 th offer? 10th offer? \(k\) th offer, \(k \geq 1 ?\) (b) If the women continue this process (providing many, many new asking prices and counteroffers), what price will they approach? (c) Suppose that Narmada was willing to buy the laptop for \$3200. What should she have offered to pay Renu the first time?

d) For \(n \geq 2\), show that g) Prove that for \(n \geq 2\) \(E_{n}=\sum_{i=1}^{\lfloor n / 2\rfloor}\left(\begin{array}{c}n-1 \\ 2 i-1\end{array}\right) E_{2 t-1} E_{n-2 k}, \quad E_{0}=E_{1}=1 . \quad E_{n}=\left(\frac{1}{2}\right) \sum_{i=0}^{n-1}\left(\begin{array}{c}n-1 \\\ i\end{array}\right) E_{1} E_{n-1-1}, \quad E_{0}=E_{1}=1\) e) Where do we find 1 in a rise/fall permutation of h) Use the result in part (g) to find \(E_{6}\) and \(E_{7}\). \(1,2,3, \ldots, n ?\) f) For \(n \geq 1\), show that i) Find the Maclaurin series expansion for \(f(x)=\sec x+\) \(\tan x\). Conjecture (no proof required) the sequence for \(E_{n}=\sum_{i=0}^{\lfloor(n-1) / 2]}\left(\begin{array}{c}n-1 \\ 2 i\end{array}\right) E_{2} E_{n-2 i-1}, \quad E_{0}=1$$\mathrm{A}\) one-to-one function \(f:\\{1,2,3, \ldots, n\\} \rightarrow\\{1,2,3\) \(\ldots, n\\}\) is often called a permutation. Such a permutation is termed a rise/fall permutation when \(f(1)f(3)\) \(f(3)1\)

For \(n>1\), a permutation \(p_{1}, p_{2}, p_{3}, \ldots, p_{n}\) of the integers \(1,2,3, \ldots, n\) is called orderly if, for each \(i=1,2,3, \ldots\) \(n-1\), there exists a \(j>i\) such that \(\left|p_{J}-p_{l}\right|=1\). [If \(n=2\), the permutations 1,2 and 2,1 are both orderly. When \(n=3\) we find that \(3,1,2\) is an orderly permutation, while \(2,3,1\) is not. (Why not?)] (a) List all the orderly permutations for \(1,2,3\). (b) List all the orderly permutations for \(1,2,3,4\). (c) If \(p_{1}, p_{2}, p_{3}, p_{4}, p_{5}\) is an orderly permutation of \(1,2,3,4,5\), what value(s) can \(p_{1}\) be? (d) For \(n>1\), let \(a_{n}\) count the number of orderly permutations for \(1,2,3, \ldots, n\). Find and solve a recurrence relation for \(a_{n}\).

In Exercise 12 of Section \(4.2\) we leamed that \(F_{0}+F_{1}+\) \(F_{2}+\cdots+F_{n}=\sum_{i=0}^{n} F_{i}=F_{n+2}-1\). This is one of many such properties of the Fibonacci numbers that were discovered by the French mathematician François Lucas (1842-1891). Although we established the result by the Principle of Mathematical Induction, we see that it is easy to develop this formula by adding the system of \(n+1\) equations $$ \begin{aligned} F_{0} &=F_{2}-F_{1} \\ F_{1} &=F_{3}-F_{2} \\ \cdots & \ldots, \quad \cdots \\ F_{n-1} &=F_{n+1}-F_{n} \\ F_{n} &=F_{n+2}-F_{n+1} \end{aligned} $$Develop formulas for each of the following sums, and then check the general result by the Principle of Mathematical Induction. a) \(F_{1}+F_{3}+F_{3}+\cdots+F_{2 n-1}\), where \(n \in \mathbf{Z}^{+}\) b) \(F_{0}+F_{2}+F_{4}+\cdots+F_{2_{x}}\), where \(n \in \mathbf{Z}^{+}\)

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