Proving Recurrence Relations and Set Elements: T Function and Natural Numbers

In summary, we define a function T : \Bbb{N} -> \Bbb{N}, such that T(2k+1) = 2k+2 and T(2k) =k. We can prove that for every n\in\Bbb{N}, there exists a positive integer k, such that T^k(n)=1 by defining the function f(x) : \Bbb{N} -> \Bbb{N}; f(2x+1)=T^2(2x+1)=x+1 and showing that {d}_{i} will continue to become smaller and smaller until it is 1. We also see that the number of elements in the set {
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IHateFactorial
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We define a function T : \(\displaystyle \Bbb{N}\) -> \(\displaystyle \Bbb{N}\), such that \(\displaystyle T(2k+1) = 2k+2\) and \(\displaystyle T(2k) =k\). Also, \(\displaystyle T^2(n)=T(T(n))\), and generally: \(\displaystyle T^k(n)={T}^{k-1}(T(n))\).

a) Prove that for every \(\displaystyle n\in\Bbb{N}\), there exists a positive integer k, such that \(\displaystyle T^k(n)=1\)

b) We say \(\displaystyle {c}_{k}\) is the number of elements in the set:

{\(\displaystyle n:T^k(n)=1\)}

Prove that \(\displaystyle {c}_{k+2}={c}_{k+1}+{c}_{k}\), for all \(\displaystyle 1\le k\).

a) We can begin by defining the function T as

\(\displaystyle T(n)=n+1\), if n is odd, and
\(\displaystyle T(n)=\frac{n}{2}\), if n is even.

Therefore, we begin at k=0 and n being some natural. If n is even, we begin by dividing by 2 until n is odd or 1, in which case we are done. We add 1 to k everytime we divide by 2. We call the number left over by dividing 2 (or the original in case it wasn't even) \(\displaystyle {d}_{0}\).

We define a function \(\displaystyle f(x) : \Bbb{N}\) -> \(\displaystyle \Bbb{N}; f(2x+1)=T^2(2x+1)=x+1\). From here we can see that f(x) will always give a value less than the original while still providing a natural number, for all 2x+1>1.

We run d through f(x) and we add 2 to k. We call the output \(\displaystyle {d}_{1}\).

\(\displaystyle {d}_{1}\) can be either odd or even. We divide \(\displaystyle {d}_{1}\) by 2 until it is odd or one, again. Each time we do so, we add 1 to k.

We can see a recurring pattern forming. \(\displaystyle {d}_{i}\) Will continue to become smaller and smaller until it is the smallest possible natural: 1.

b) We see that \(\displaystyle {c}_{1}\) = 1. {2}
\(\displaystyle {c}_{2}\) = 2. {1, 4}
\(\displaystyle {c}_{3}\) = 3. {2, 3, 8}
\(\displaystyle {c}_{4}\) = 5 {1, 4, 6, 7, 16}

We conclude two things:

The number of even numbers in set \(\displaystyle {c}_{k+1}\) is equal to the number of elements in \(\displaystyle {c}_{k}\). This is because every even number in \(\displaystyle {c}_{k}\) comes from one number in \(\displaystyle {c}_{k-1}\). (We denote the number of even numbers in \(\displaystyle {c}_{k}\) as \(\displaystyle {e}_{k}\)).

\(\displaystyle {e}_{k+1}\) = \(\displaystyle {c}_{k}\)

The number of elements in \(\displaystyle {c}_{k+1}\) equals double the number of even numbers in the last set plus the number of odds in the last set. Reason: Each even number "leads" to two numbers (an odd and an even) and every odd number leads to an even. (We denote the number of odds in \(\displaystyle {c}_{k}\) as \(\displaystyle {o}_{k}\)).

\(\displaystyle 2{e}_{k}+{o}_{k}={c}_{k+1}\)With these defintions:

\(\displaystyle {c}_{k+2}={c}_{k+1}+{c}_{k}\)

\(\displaystyle 2{e}_{k+1}+{o}_{k+1}={e}_{k+1}+{o}_{k+1}+{c}_{k}\)

\(\displaystyle {e}_{k+1}={c}_{k}\)

The above step is an identity and such, it is proven.
 

FAQ: Proving Recurrence Relations and Set Elements: T Function and Natural Numbers

What is a recurrence relation?

A recurrence relation is a mathematical equation that defines a sequence of numbers or mathematical objects by relating each term to one or more of the previous terms. It is often used in analyzing recursive algorithms and solving problems in combinatorics and number theory.

What are the types of recurrence relations?

The two main types of recurrence relations are linear and nonlinear. A linear recurrence relation has the form an = c1an-1 + c2an-2 + ... + ckan-k, where c1, c2, ..., ck are constants and n is the index of the term. Nonlinear recurrence relations involve more complex relationships between the terms.

What is the difference between a recurrence relation and a recursive algorithm?

A recurrence relation is a mathematical equation that defines a sequence, while a recursive algorithm is a step-by-step procedure for solving a problem that involves repeating the same steps with different inputs. Recurrence relations are often used to analyze the time complexity of recursive algorithms.

What is the importance of recurrence relations in computer science?

Recurrence relations are important in computer science because they are used to analyze the time complexity of recursive algorithms, which are commonly used in computer programs. They also have applications in data structures, graph theory, and other areas of computer science.

How can recurrence relations be solved?

There are several methods for solving recurrence relations, including substitution, iteration, and generating functions. These methods involve manipulating the recurrence relation in order to find a closed form solution, which expresses the terms of the sequence directly in terms of n without any recursive definitions.

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