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Q. Time Complexity of the following CPP code will be order of O()?
int a = 0;
for (i = 0; i < N; i++) {
for (j = N; j > i; j--) {
a = a + i + j;
}
}
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- 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 examplesGenerate a graph of performance improvement for code below. Tip: Figure 5.17 in the textbook provides an example of a graph depicting performance improvements associated with loop unrolling. code: //normal code int main() { int n, sum=0; n=50; int a[50]; { for(int i=0; i<n; i++) { sum= sum +a[i]; } printf("sum is %d", sum); return 0; } //with unrolling int main() { int n, sum=0; n=50; int a[50] for(int i=0; i<n; i+=10) { scanf("%d", &a[i]); } sum= sum + a[0]; sum= sum + a[1]; sum= sum + a[2]; sum= sum + a[3]; sum= sum + a[4]; sum= sum + a[5]; sum= sum + a[6]; sum= sum + a[7]; sum= sum + a[8]; sum= sum + a[9]; printf("sum is %d", sum); return 0; }What is the running time for this java code? I want the complexity and asymptotic upper bound using Big-Oh notation class lcs { static void LongestCommonArraySubsequence(int X[], int Y[], int n, int m) { // dp[][] array int[][] dp = new int[n + 1][m + 1]; // dp matrix initialization for (int i = 0; i <= n; i++) for (int j = 0; j <= m; j++) dp[i][j] = 0; for (int i = n - 1; i >= 0; i--) { for (int j = m - 1; j >= 0; j--) { if (X[i] == Y[j]) dp[i][j] = dp[i + 1][j + 1] + 1; // bottom up fill } } int max = 0; // maximum length int Xindex = 0; // starting index of array X int Yindex = 0; // starting index of array Y for (int i = 0; i < n; i++) { for (int j = 0; j < m; j++) { // calculating the maximum value in dp matrix if (dp[i][j] > max) {…
- 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.This is a MATLAB Coding problem: Implement a recursive function, called count, that takes two inputs, an array of integers and target integer. count should search the array for the target integer and return the number of occurrences of the target integer in the array. For example: disp(count([1, 2, 4, 1, 2, 1], 1)) % Generates 3disp(count([1, 2, 4, 1, 2, 1], 2)) % Generates 2disp(count([1, 2, 4, 1, 2, 1], 4)) % Generates 1disp(count([1, 2, 4, 1, 2, 1], 9000)) % Generates 0Please answer this, thanks! 1. give the analysis of the running time (Big-Oh will do) and the space complexity. b. please 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. (3) sum = 0;for( i = 0; i < n; ++i )for( j = 0; j < i * i; ++j )for( k = 0; k < j; ++k ) ++sum;
- 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?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;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
- Although the A* algorithm performs better with a more educated heuristic function, the overall computation time with a less informed heuristic can be reduced. How is that possible?What is the leading term for the following expressions and specify the lowest Big O Complexity for each algorithm?Calculate Cyclomatic complexity for the given code for (i=0 ; i<=N ; i++)p[i] = 1;for (i=2 ; i<=N ; i++){k = p[i]; j=1;while (a[p[j-1]] > a[k] {p[j] = p[j-1];j--;}p[j]=k;}
