1.1 Calculate the total number of steps required by the algorithm, and express it as a function of n (f(n) ). 1.2 Determine the Time complexity of the algorithm using Big-O notation. O(n) the highest power of n
1.1 Calculate the total number of steps required by the algorithm, and express it as a function of n (f(n) ). 1.2 Determine the Time complexity of the algorithm using Big-O notation. O(n) the highest power of n
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Transcribed Image Text:1.1 Calculate the total number of steps required by the algorithm, and express it as a
function of n (fln)).
1.2 Determine the Time complexity of the algorithm using Big-O notation.
O(n) the highest power of n
![# 3x3 matrix
X = [[12, 7, 3],
[4, 5, 6],
[7, 8, 9]]
# 3x4 matrix
Y = [[5, 8, 1, 2],
[6, 7, 3, 0],
[4, 5, 9, 1]]
%3D
# empty matrix to store the result
Z = [[0, 0, 0, 0],
[0, о, о, е],
[0, е, в, е]]
%3D
def MatrixMultiplication(A,B,C):
# iterating by row of A
for i in range(len(A)):
# iterating by columns by B
for j in range(len(B[0])):
# iterating by rows of B
for k in range(len(B)):
C[i][j] += A[i][k] * B[k][j]
for r in C:
print(r)
# function call
MatrixMultiplication(X,Y,z)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fbef7fb9e-2ef5-4d38-a308-c822a986d1cc%2Fdb3fa864-78a2-4988-bd86-c7d2120956f5%2Fi9wcemo_processed.jpeg&w=3840&q=75)
Transcribed Image Text:# 3x3 matrix
X = [[12, 7, 3],
[4, 5, 6],
[7, 8, 9]]
# 3x4 matrix
Y = [[5, 8, 1, 2],
[6, 7, 3, 0],
[4, 5, 9, 1]]
%3D
# empty matrix to store the result
Z = [[0, 0, 0, 0],
[0, о, о, е],
[0, е, в, е]]
%3D
def MatrixMultiplication(A,B,C):
# iterating by row of A
for i in range(len(A)):
# iterating by columns by B
for j in range(len(B[0])):
# iterating by rows of B
for k in range(len(B)):
C[i][j] += A[i][k] * B[k][j]
for r in C:
print(r)
# function call
MatrixMultiplication(X,Y,z)
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