A binary tree is full if all of its vertices have either zero or two children. Let Bndenote the number of full binary trees with n vertices. (a)By drawing out all full binary trees with 3, 5, or 7 vertices, determine the exact values of B3, B5, and B7. Why have we left out even numbers of vertices, like B4?

(b) For general n, derive a recurrence relation for Bn.

(c) Show by induction that Bnis Ω(2n).

Short Answer

Expert verified

(a) Exact value of B3=1

Exact value of B5=2

Exact value of B7=5

(b) Required recurrence relation: Bn=i=1n-2BiBn-i-1

(c) By induction, it is proved that Bn=Ω2n

Step by step solution

01

Solution of part (a)

All binary trees having 3, 5, and 7 nodes are shown in following diagrams:

The following is a binary tree with three verticesB3:

From either the multiple endpoints, only one full binary tree can be drawn.

As a result, the precise value ofB3is 1.

B3=1

The binary tree with five verticesB5is shown below:

Here, two binary trees can be drawn from the five vertices. Therefore, the exact value ofB5is 2 .

The binary tree with five verticesB7is shown below:

From of the seven edges, five binary trees may be drawn. As a result, the precise value ofB7is 5.

The number of edges in a complete binary tree must be odd.

As a result, there is no requirement forB4or B6etc.

02

Solution of part (b)

Recurrence relation for Bnis given below:

The number of entire binary trees is equal to the total of the products of something like the series of binary trees from the child trees.

Bn=i=1n-2BiBn-i-1

That number of sensor nodes inside the left sub-tree is I while the number of nodes in the right sub-tree is n-i-1.

When n=5 is the number of vertices in a binary tree, the precise value of B5is given as follows:

B5=i=15-2BiB5-i-1=B1B3+B2B2+B3B1=1+0+1=2

As a result, there are two binary trees produced for every five vertices.

As a result, the recurrence relation is shown to be valid Bn=i=1n-2BiBn-i-1

03

Solution to part (c)

The proof is as follows:

Display that,Bn2n-32

Base case:

n=1B1=12-1B3=12°

Inductive steps:

For n3odd:

Bn+2=i=1n+1BiBn-i-1n+22×2n-5222n-52=2n-12

Thus, it is proved that Bn would be Ω(n2).

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Most popular questions from this chapter

How many lines, as a function of n (in (.)form), does the following program print? Write a recurrence and solve it. You may assume is a power of . function f (n) if n > 1:

print_line (‘‘still going’’)

f (n/2)

f (n/2)

In this problem we will develop a divide-and-conquer algorithm for the following geometric task.

CLOSEST PAIRInput: A set of points in the plane, {p1=(x1;y1),p2=(x2,y2),...,pn=(xn,yn)}

Output: The closest pair of points: that is, the pair PiPjfor which the distance between piand pj, that is,

(xi-xi)2+z(yi-yi)2,

is minimized.

For simplicity, assume that n is a power of two, and that all the x-coordinates role="math" localid="1659237354869" xi are distinct, as are the y-coordinates.

Here’s a high-level overview of the algorithm:

.Find a value for which exactly half the points have xi<x, and half have xi>x. On this basis, split the points into two groups, L and R.

• Recursively find the closest pair in L and in R. Say these pairs are pL·qLLand pR·qRRwith distances dLand dR respectively. Let d be the smaller of these two distances.

• It remains to be seen whether there is a point in Land a point in R that are less than distance dapart from each other. To this end, discard all points with xi<x-dor xi>x+d and sort the remaining points by y-coordinate.

• Now, go through this sorted list, and for each point, compute its distance to the seven subsequent points in the list. Let pM·qMbe the closest pair found in this way.

• The answer is one of the three pairs role="math" localid="1659237951608" {pL,qL},{pR,qR}{pM,qM}, whichever is closest.

(a) In order to prove the correctness of this algorithm, start by showing the following property: any square of size d×d in the plane contains at most four points of L.

(b) Now show that the algorithm is correct. The only case which needs careful consideration is when the closest pair is split between L and R.

(c) Write down the pseudocode for the algorithm, and show that its running time is given by the recurrence:

T(n)=2T(nl2)+0(nlogn)

Show that the solution to this recurrence is o(nlogzn).

(d) Can you bring the running time down to O(nlogn)?

What is the sum of the nth roots of unity? What is their product if n is odd? If n is even?

An array A[1...n] is said to have a majority element if more than half of its entries are the same. Given an array, the task is to design an efficient algorithm to tell whether the array has a majority element, and, if so, to find that element. The elements of the array are not necessarily from some ordered domain like the integers, and so there can be no comparisons of the form “ is A[i]>A[j] ?”. (Think of the array elements as GIF files, say.) However you can answer questions of the form: “is ..?” in constant time.

(a) Show how to solve this problem in O(nlogn) time. (Hint: Split the array A into two arrays A1and A2of half the size. Does knowing the majority elements of A1and A2help you figure out the majority element of A? If so, you can use a divide-and-conquer approach.)

(b) Can you give a linear-time algorithm? (Hint: Here’s another divide-and-conquer approach:• Pair up the elements of A arbitrarily, to get n/2 pairs• Look at each pair: if the two elements are different, discard both of them; if they are the same, keep just one of them . Show that after this procedure there are at most n/2 elements left, and that they have a majority element if A does.)

Practice with the fast Fourier transform.

(a) What is the FFT of (1,0,0,0)? What is the appropriate value of ωin this case? And of which sequence is (1,0,0,0)the FFT?

(b)Repeat for (1,0,1,-1).

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