4. (20 points) For each of the following recurrences, give an expression for the runtime T(n)...
1. [12 marks] For each of the following recurrences, use the “master theorem” and give the solution using big-O notation. Explain your reasoning. If the “master theorem” does not apply to a recurrence, show your reasoning, but you need not give a solution. (a) T(n) = 3T(n/2) + n lg n; (b) T(n) = 9T(3/3) + (n? / 1g n); (c) T(n) = T([n/41) +T([n/4])+ Vn; (d) T(n) = 4T([n/7])+ n.
Algorithms: Please explain each step! Thanks! (20 points) Use the Master Theorem to solve the following recurrence relations. For each recurrence, either give the asympotic solution using the Master Theorem (state which case), or else state the Master Theorem doesn't apply (d) T(n) T() + T (4) + n2 (20 points) Use the Master Theorem to solve the following recurrence relations. For each recurrence, either give the asympotic solution using the Master Theorem (state which case), or else state the...
5) For each of the following recurrences state whether the Master theorem can be applied to solve the recurrence or not. If the Master theorem can be used, then use it to determine running time for the recurrence. If the Master theorem cannot be applied, then specify the reason (you don't need to solve the recurrence). a) T(n) = 4T(n/3)+n2
Question 6 (20 points) Solve the following recurrences using the Master Theorem. T(n) = 2T (3/4)+1 T(n) = 2T (n/4) + va 7(n) = 2T (n/4) +n T(n) = 2T (3/4) + n
Using the Master Method give asymptotic bounds for T(n) in each of the following recurrences. Assume that T(n) is constant for n ≤ 4. (a) T(n) = 4 T(n/4) + n lg2 n (b) T(n) = 3 T(n/4) + n lg n c) T(n) = 4 T(n/5) + √? (d) T(n) = 4 T(n/2) + n2 lg n
Give asymptotic upper and lower bounds for T(n) in each of the following recurrences. Assume that T(n) is constant for n ≤ 3. Make your bounds as tight as possible, and justify your answers. 5.a T(n) = 2T(n/3) + n lg n 5.b T(n) = 7T(n/2) + n3 5.c T(n) = 3T(n/5) + lg2 n
Give the asymptotic bounds for T(n) in each of the following recurrences. Make your bounds as tight as possible and justify your answers. Assume the base cases T(0)=1 and/or T(1) = 1. 1. T(n) = T(n-1) + 2n 2. T(n) = T(n-2) = 3
Give asymptotic upper and lower bounds for T(n)in each of the following recurrences. Assume that T(n)is constant forn≤10. Make your bounds as tight as possible, and justify your answers. 1.T(n)=3T(n/5) +lg^2(n) 2.T(n)=T(n^.5)+Θ(lglgn) 3.T(n)=T(n/2+n^.5)+√6046 4.T(n) =T(n/5)+T(4n/5) +Θ(n)
Give asymptotic upper and lower bounds for T(n) in each of the following recurrences. Assume that T(n) is constant for n≤2. Make your bounds as tight as possible, and justify your answer. *Hint : You can use Master method to obtain Θ(.). (a) T(n) = 4T(n/4) + 5n (b) T(n) = 4T(n/5) + 5n (c) T(n) = 5T(n/4) + 4n (d) T(n) = 25T(n/5) + n^2 (e) T(n) = 4T(n/5) + lg n (f) T(n) = 4T(n/5) + lg^5 n...
T(n) = aT(n/b)+O(nd) T(n) = 4T(n/2) + 5nlogn a = 4, b = 2, d = ? <----I don't know how to find d If d > logba, then T(n) = O(nd) If d = logba, then T(n) = O(nd logn) If d < logba, then T(n) = O(nlogba) Question 5 What is the tightest bound the Master Theorem can put on this recurrence relation? T(n) 4 T(n/2) 5n log n O O 1.1 O o(n2 og n o(n2) O(n)...