4. fun(n) if (n <= 1) return 1 for i=n it=2 f(n-1) + f(n-2) +f (n-3)... i/=n
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- reflection how to analyze time complexity of an algorithm by using suitable example.) Implement a quicksort with a 2k-sample-size-based sample. The sample should be sorted first, after which you should set up the recursive procedure to split the sample based on its median and to shift the two halves of the remaining sample to each subarray so they can be utilised in the subarrays without needing to be sorted again. The name of this algorithm is samplesort.Modeling the spread of a virus like COVID-19 using recursion. Let N = total population (assumed constant, disregarding deaths, births, immigration, and emigration). S n = number who are susceptible to the disease at time n (n is in weeks). I n = number who are infected (and contagious) at time n. R n = number who are recovered (and not contagiuous) at time n. The total population is divided between these three groups: N = S n + I n + R n There are several hidden assumptions here that may or may not apply to COVID-19, such as a recovered person is assumed to not be able to get the disease a second time, at least within the time window being examined. On week 0 (the start), you assume a certain small number of people have the infection (just to get things going). Everyone else is initially susceptible, and no one is recovered. There are two constants of interest: Let period = time period that it takes for an infected person to recover (recover meaning they become not infectious to…
- Consider a divide-and-conquer algorithm that calculates the sum of all elements in a set of n numbers by dividing the set into two sets of n/2 numbers each, finding the sum of each of the two subsets recursively, and then adding the result. What is the recurrence relation for the number of operations required for this algorithm? Answer is f(n) = 2 f(n/2) + 1. Please show why this is the case.The binomial coefficient C(N,k) can be defined recursively as follows: C(N,0) = 1, C(N,N) = 1, and for 0 < k < N, C(N,k) = C(N-1,k) + C(N - 1,k - 1). Write a function and give an analysis of the running time to compute the binomial coefficients as follows: A. The function is written recursively.What is the leading term for the following expressions and specify the lowest Big O Complexity for each algorithm?
- Implement a quicksort with a sample size of 2k 1. Sort the sample first, then have the recursive procedure partition on the sample's median and shift the two halves of the rest of the sample to each subarray so that they may be utilised in the subarrays without having to be sorted again. This algorithm is known as samplesort. Put into practise a quicksort based on a 2k sample. The sample should be sorted first, after which you should set up the recursive procedure to split the sample based on its median and to shift the two halves of the remaining sample to each subarray so they can be utilised in the subarrays without needing to be sorted again. The name of this algorithm is samplesort.Suppose that your implementation of a particular algorithm appears in C++ as for (int pass = 1; pass <= n; pass++) { for (int index = 0; index < n; index++) { for (int count = 1; count < 10; count++) { ... } // end for } // end for } // end for The previous code shows only the repetition in the algorithm, not the computations that occur within the loops. These computations, however, are independent of n. What is the Big O of the algorithm?What is the time complexity of the following function- 5T(n/5+50)+n,T(1)=1 (a) θ(50logn) (b) θ(n50logn) (c) θ(logn) (d) θ(nlogn) (e) θ(nlogn)
- Give an example of an algorithm that is O(1), an algorithm that is O(n) and an algorithm that is O(n2). Discuss the difference between them.Do a Word Ladder with Python. Given two words(begin,end) and a dictionary's word list, find the length of shortest transformation sequence and print out the transfor words. 1.Only one letter can be changed at a time 2. Each transformed word must exist in the word list Example1: Input: begin="hit" end="cog" wordList=["hot","dog","dot","lot","log","cog"] output: hit->hot->dot->dog->cog length is 5a) Consider a recursive function to return the Number of Binary Digits in the Binary Representation of a Positive Decimal Integer (n) using a recursive algorithm. int Process (int n) { if (n == 1) return 1; else return (Extra() + Process (n/4) + Process (n/4)); } Given that Extra(n) is a function of O(n)1) Find T(n) = number of arithmetic operations. 2) Calculate the complexity of this algorithm using Back Substitution.