efficiencies of the three approaches above can be compared for different relationships between m and n.   If m > log n, which approach is the most efficient in the average case?  Why? If m < log n, which approach is the most efficient in the average case?  Why?

Express the solution in big-O terms for the following recurrence relation: T(n) = 9*T(n/3) + n^3; T(1)=1; Answer: T(n) = O(......) .

What is the recurrence relation of maximum subarray sum problem by using Divide and Conquer approach CHOOSE ANY ONE OPTION    1.T(n) = 7T(n/2) + n 2.T(n) = 8T(n/2) + n 3.T(n) = 2T(n/2) + n 4.T(n) = T(n/2) + n

Please follow bartleby guidelines and answer the two questions.

Use an Euler diagram to determine validity: All professional comedians are funny.  Some funny people are math professors.  Therefore some professional comedians are math professors.

Question 4: Consider two recurrence relations P(n) = 2P(n/2) +n and Q(n) = 4Q (n/4) +2n. What is the relationship between P and Q? Is P = O(Q), P = N(Q), or P = O(Q)? Prove your answer using limit of ratio definition of asymptotic notations.

Express the solution in big-O terms for the following recurrence relation: T(n) = 9*T(n/3) + n^3; T(1)=1; Answer: T(n) = O(......) .

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The time complexity equation of merger-sort is T(n) = 2* T(n/2) + n, where T(1) = C and C is a constant. Solve this equation by giving detailed steps.  2. The time complexity equation of merger-sort T(n) = 3* T(n/3) + n, where T(1)=T(2)=C, what would be T(n)?   Please do the 2 question only, thanks

Is this answer correct? It seems as if you mention that 2^(f(n)) is always an upper bound for 2^(c*g(n)), which is not right consider the statement (should be the other way around). Also, how does this statement, "Since 2 f(n) is an exponential function with a positive base, it grows much faster than any polynomial function g(n)." give us any inference on the upper bound?