Calculate the time complexity of the following programming codes. (a). while (n > 2) { n = v25 } (b). for (i=1; i<= n; i++) for (j=1; j<= n; j++) { a = b + c;
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- Please answer this, thanks! a. give the running time (Big-Oh) and the space complexity. b. implement the code in the language of your choice and give the running time for three values of N (N must be >; 5). c. Compare your analysis with the actual running times. (1) sum = 0;for( i = 0; i < n; ++i )++sum;Design pushdown automata and turing machine for SQUARE = { a^n where n is a square}The language must be in python. Just do numbers 5-7 Neural Network Units Implement a single sigmoid neural network unit with weights of [-1.2, -1.1, 3.3, -2.1] Calculate the outputs for two training examples:Example 1: [0.9, 10.0, 3.1, 1]Example 2: [0.9, 2.1, 3.7, 1] Note that you don't have to explicitly include a threshold or bias since the examples include a last element of 1 which means that the last weight effectively operates as a threshold. Assuming that a sigmoid unit response >0.5 denotes a positive class and <0.5 is negative class, is example 1 positive or negative? is example 2 positive or negative? Create a single ReLU unit and provide the outputs for those examples. Calculate the derivative of the sigmoid with respect to net input for both examples Calculate the derivative of the ReLU with respect to net input for both examples
- Explain, by way of an example, how Dynamic Programming with Memoisation improves the complexity of an algorithm you have seen in lectures. In your answer be sure to say what the algorithm complexity would be without memoisation.Any clearly defined computational process that receives a value or set of values as input and produces a value or set of values is known as an algorithm. Is it feasible to compare and contrast two different methods that address the same issue? Provide a brief explanation of the optimisation metrics or algorithm.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 using dynamic programming.
- The language for coding must be in python Neural Network Units Implement a single sigmoid neural network unit with weights of [-1.2, -1.1, 3.3, -2.1] Calculate the outputs for two training examples:Example 1: [0.9, 10.0, 3.1, 1]Example 2: [0.9, 2.1, 3.7, 1] Note that you don't have to explicitly include a threshold or bias since the examples include a last element of 1 which means that the last weight effectively operates as a threshold. Assuming that a sigmoid unit response >0.5 denotes a positive class and <0.5 is negative class, is example 1 positive or negative? is example 2 positive or negative? Create a single ReLU unit and provide the outputs for those examples. Calculate the derivative of the sigmoid with respect to net input for both examples Calculate the derivative of the ReLU with respect to net input for both examplesDevelop two algorithms, one based on a loop structure and the other on a recursive structure, to print the daily salary of a worker who each day is paid 2.5 times the previous day’s salary (starting with one penny for the first day’s work) for a 30-day period. What problems relating to number storage are you likely to encounter if you implement your solutions on an actual machine?Construct a memoized algorithm for this algorithm and and derive its time complexity: Assume that you were given N cents (N is an integer) and you were asked to break up the N cents into coins consisting of 1 cent, 2 cents and 5 cents. Write a dynamicprogramming based recursive algorithm, which returns the smallest (optimal) number of coins needed to solve this problem. For example, if your algorithm is called A, and N = 13, then A(N) = A(13) returns 4, since 5+5+2+1 = 13 used the smallest (optimal) number of coins. In contrast, 5+5+1+1+1 is not an optimal answer. You do not need to prove the complexity bound formally, just derive it by analyzing each component in your algorithm.
- 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…please answer this. thanks a. Give analysis of the running time (Big-Oh will do) and the space complexity. b. Implement the code in C language and give the running time for threevalues of N (N must be > 5). c. Compare your analysis with the actual running times. (3.) sum = 0; for( i = 0; i < n; ++i ) for( j = 0; j < i * i; ++j ) for( k = 0; k < j; ++k ) ++sum;Information is present in the screenshot and below. Based on that need help in solving the code for this problem in python. The time complexity has to be as less as possible (nlogn or n at best, no n^2). Apply dynamic programming. Do not use recursion/memoization. Make sure ALL test cases return expected outputs. Sample Input 04 412340123 Sample Output 013715 Explanation 0You are given the sequence 1,2,3,4.F0 = A0 = 1F1 = A1 + F0 = 2 + 1 = 3F2 = A2 + F1 + F0 = 3 + 3 + 1 = 7F3 = A3 + F2 + F1 + F0 = 4 + 7 + 3 + 1 = 15 The actual code def solve(k,a): MOD = 1000000007 # compute and return answer here q, n = list(map(int,input().rstrip().split(" ")))a = [int(input().rstrip()) for i in range(n)]outs = []for i in range(q): k = int(input().rstrip()) outs.append(solve(k,a))print("{}".format("\n".join(list(map(str,outs)))))
