Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

Show that for any positive integers n and any base b , there must some power of b lying in the range [b,bn].

Short Answer

Expert verified

To show that some power of b falls in the range of n,bn

Step by step solution

01

Introduction

With each integer values n and so any base b , basic process of designing algorithms is used to argue that there must be some power of b lying in the range n,bn. Each algorithm's execution duration is determined by the randomness of our inputs.

In the above question any positive integers either it is n and any base as b , it must be power of b lying with the range of n and bn . To check or understand see base information theory.

Condition of origin:

Here,n is a positive integer and b would be any base, as shown by numerically solving.

Assume n=1 and b as the basis.

As a result, there is a power of b that falls inside the range1,b .

02

Proving

Hypothesis via Induction:

Look at the fact that for each given base number b and n=k, there must be a factor of b inside the range k,bk.

Within interval k,bk, there persists a strength of b , say, bp , for some base b and positive integer k .

The proof:

Its proven assertion holds with n=k+1, i.e., for each set of base number b, a power of b within range k+1,bk+1 exists at all times.

To get all the bottom limits' area, do the following:

By inductive inference, if bp>k, then k is a positive integer and bp should be in the range k,bk.

As a result, the following integer as in k value is k+1 .

As a result, the sentence bp>kmay be written bpk+1.

To have the higher boundaries' area, do the following:

Assume the logical premise bp=k .

Multiply either system of equations by b.

This is undeniably true.

bbp=bkbk<bk+1bbp<bk+1bp+1<bk+1k+1bpbp+1<k+1k+1bp<bk+1

As a result, it is shown that for each positive integer k+1 and b , there exists some power of b in the region k+1,bk+1.

As a result, there exists some power of b in the range n,bn for each positive integer n and also any base b.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Question: On page 66 there is a high-level description of the quicksort algorithm.

(a) Write down the pseudocode for quicksort.

(b) Show that its worst - case running time on an array of size n is Θ(n)2.

(c) Show that its expected running time satisfies the recurrence relation.

T(n)O(n)+1ni=1n-1(Ti+Tn-i)

Then, show that the solution to this recurrence is O(nlogn).

In justifying our matrix multiplication algorithm (Section 2.5), we claimed the following block wise property: if X and Y are n×nn matrices, and

X=[ABCD],Y=[EFGH],

where A,B,C,D,E,F,G, and H are n/2×n/2 sub-matrices, then the product XY can be expressed in terms of these blocks:

XY=[ABCD][EFGH]=[AE+BGAF+BHCE+DGCF+DH]

Prove this property.

Section 2.2 describes a method for solving recurrence relations which is based on analyzing the recursion tree and deriving a formula for the work done at each level. Another (closely related) method is to expand out the recurrence a few times, until a pattern emerges. For instance, let’s start with the familiar T(n)=2T(n/2)+o(n). Think of o(n) as being role="math" localid="1658920245976" <cnfor some constant , so: T(n)<2T(n/2)+cn. By repeatedly applying this rule, we can bound T(n) in terms of T(n/2), then T(n/4), then T(n/8), and so on, at each step getting closer to the value of T(.) we do know, namely .

T(1)=0(1).

T(n)2T(n/2)+cn2[2Tn/4+cn/2]+cn=4T(n/4)+2cn4[2Tn/8+cn/4]+2cn=8T(n/8)+3cn8[2Tn/16+cn/8]+3cn=16T(n/16)+4cn

.

.

.

A pattern is emerging... the general term is

T(n)2kT(n/2k)+kcn

Plugging in k=log2n, we get T(n)nT(1)+cnlog2n=0(nlogn).

(a)Do the same thing for the recurrence T(n)=3T(n/2)+0(n). What is the general kth term in this case? And what value of should be plugged in to get the answer?(b) Now try the recurrence T(n)=T(n-1)+0(1), a case which is not covered by the master theorem. Can you solve this too?

A linear, time-invariant system has the following impulse response:


(a) Describe in words the effect of this system.

(b) What is the corresponding polynomial

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

See all solutions

Recommended explanations on Computer Science Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free