Write a recurrence relation describing the worst-case
running time of each of the following algorithms and determine the
asymptotic complexity of the function defined by the recurrence
relation. Justify your solution by using substitution or a
recursion tree. You may NOT use the Master Theorem.
if n <= 20 it is constant function
Otherwise recurrence relation of above algorithm is
T(n) = T(n-4) + T(n-10) +
So recurrence relation is
T(n) = T(n-4) + T(n-10) + log(n)
As shown in recurrence tree of this algorithm the worst case time complexity will be
//If you have any doubt.Please feel free to ask.Thanks.
Write a recurrence relation describing the worst-case running time of each of the following algor...
Write a recurrence relation describing the worst case running time of each of the following algorithms, and determine the asymptotic complexity of the function defined by the recurrence relation. Justify your solution by using substitution or a recursion tree. You may NOT use the Master Theorem. Simplify your answers, expressing them in a form such as O(nk) or (nklog n) whenever possible. If the algorithm takes exponential time, then just give an exponential lower bound using the 2 notation. function...
For each of the following problems write a recurrence relation describing the running time of each of the following algorithms and determine the asymptotic complexity of the function defined by the recurrence relation. Justify your solution using substitution and carefully computing lower and upper bounds for the sums. Simplify and express your answer as Θ(n k ) or Θ(n k (log n)) wherever possible. If the algorithm takes exponential time, then just give exponential lower bounds. 5. func5 (A,n) /*...
7. What is the worst-case running time complexity of an algorithm with the recurrence relation T(N) = 2T(N/4) + O(N2)? Hint: Use the Master Theorem.
For each of the following recursive methods available on the class handout, derive a worst-case recurrence relation along with initial condition(s) and solve the relation to analyze the time complexity of the method. The time complexity must be given in a big-O notation. 1. digitSum(int n) - summing the digits of integer: int digitSum(int n) { if (n < 10) return n; return (digitSum(n/10) + n%10); } 2. void reverseA(int l, int r) - reversing array: void...
2. Give the asymptotic running time of each the following functions in e notation. That is, write down a recurrence relation for each recursive function below and solve it. Show your work def Pow(x, n): 2 if n-0: 3 return 1 end 5 e f Pow(x, [n/2]) 1 # n is even if n % 2-0: 9 return f f 10 end #nis odd 12return r*f*.f 13 end
Exercise 7.3.5: Worst-case time complexity - mystery algorithm. The algorithm below makes some changes to an input sequence of numbers. MysteryAlgorithm Input: a1, a2....,an n, the length of the sequence. p, a number Output: ?? i != 1 j:=n While (i < j) While (i <j and a < p) i:= i + 1 End-while While (i <j and a 2 p) j:=j-1 End-while If (i < j), swap a, and a End-while Return( aj, a2,...,an) (a) Describe in English...
Compute the recurrence relation, T(n), for the following function, solve it, and give a e bound. Justify your answer public static double myPower(double r, int n) if (n1){ return 1 } else if (n % 2 == 0) { double tmp myPower (r, n/2); return tmp tmp; } else{ myPower (r, (n 1)/2); return }
What is the worst-case asymptotic time complexity of the following divide-andconquer algorithm (give a Θ-bound). The input is an array A of size n. You may assume that n is a power of 2. (NOTE: It doesn’t matter what the algorithm does, just analyze its complexity). Assume that the non-recursive function call, bar(A1,A2,A3,n) has cost 3n. Show your work! Next to each statement show its cost when the algorithm is executed on an imput of size n abd give the...
What is the worst-case asymptotic time complexity of the following divide-andconquer algorithm (give a Θ-bound). The input is an array A of size n. You may assume that n is a power of 2. (NOTE: It doesn’t matter what the algorithm does, just analyze its complexity). Assume that the non-recursive function call, bar(A1,A2,A3,n) has cost 3n. Show your work! Next to each statement show its cost when the algorithm is executed on an imput of size n abd give the...
Consider the following: Algorithm 1 Smallest (A,q,r) Precondition: A[ q, ... , r] is an array of integers q ≤ r and q,r ∈ N. Postcondition: Returns the smallest element of A[q, ... , r]. 1: function Smallest (A , q , r) 2: if q = r then 3: return A[q] 4: else 5: mid <--- [q+r/2] 6: return min (Smallest(A, q, mid), Smallest (A, mid + 1, r)) 7: end if 8: end function (a) Write a recurrence...