T(n) = aT (^) + f(n) F(n) = 3 F()+n, use el Teorema Maestro
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use the master theorem
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- Find a (generating matrix) for the following code and find the parameters [n, k, d], code. C = {10101010, 1100, 11110000,01100110,00111100}Function Name: odd_even_diagParameters: a 2D list (list of lists)Returns: list of lists Description: Given a 2-dimensional matrix (list of lists) with any size (n*n), modify it according to the following rules: Find the sum of the main diagonal. If the sum is an odd number, change all the values of the given matrix (except the main diagonal) to 0. If the sum is an even number, change all the values of the given matrix (except the main diagonal) to 1. Return the resulting matrix. Example 1:If argument is: [[1, 2], [4, 3]] odd_even_diag should return: [[1, 1], [1, 3]] because the sum 1 + 3 is even. Example 2:If argument is: [[1, 2, 3], [4, 5, 6], [7, 8, 9]] odd_even_diag should return: [[1, 0, 0], [0, 5, 0], [0, 0, 9]] because the sum 1 + 5 + 9 is odd.▸ Part 1 ▾ Part 2 Construct a truth table to prove if the argument is valid or invalid. The argument is Ovalid Ⓒinvalid P 9 pvq (pvq) ^p q ((pv q) ^p) →9
- Define, A = Find x. Hint: use numpy.linalg.inv and the @operator for matrix multiplication. 3 6 2 b = 10 5 2 1 7 5 Y = 3 Ax + b = Y Nif A=[1 10 30 ; 5 -1 3] choose the correct code to get the matrix B =[10 ;-1]: None of above B=A(1,:) B=A(:,2) O B=A(2,:)t(1) = 5 , t(n) = t(n/2) substitution recurrence relation
- x^2+y^2+z^2=9 how I can plot this function in pyton matplotlib (I need pyton code)The function reshape(A,r,c) is used to: In matllab reshapes A in to r column and c rows reshapes A in to r rows and c columns Other:The formula C=numpy.add(A, B) adds the two matrices A and B and stores the result in C.• To subtract matrix B from matrix A, enter C=numpy.subtract(A, B). The result is stored in C.• C=numpy.divide(A, B): Split matrix A into two equal parts and store the result in C.• C stands for numpy.multiply(A, B): Multiply matrices A and B, then store the result in matrices C.• C=numpy.sum(A): Calculate the sum of each element in the matrix A, then store the result in c R.• C=numpy.sum(A, axis = 0): Create a vector C by adding the columns of the matrix A.• C=numpy.sum(A, axis = 1): Summarize matrix A row-by-row and store the result in the vector C. Create Python code that demonstrates the use of these techniques in a sample matrix.