Data Structures and Algorithms - Performance Analysis of Algorithms and Recurrences

Avatto > > UGC NET COMPUTER SCIENCE > > PRACTICE QUESTIONS > > Data Structures and Algorithms > > Performance Analysis of Algorithms and Recurrences

27. What is the generating function G(z) for the sequence of Fibonacci numbers?

  • Option : C
  • Explanation :
    Assuming Fibonacci Sequence as :- 1, 1, 2, 3, 5, 8, 13, ......
    So, sequence an = 1,1,2,3,5,8,13,… where, n=0,1,2,3,…
    Now, The Generating Function for the sequence an of real numbers is defined as:

    So, For the given Fibonacci Series :-
    ⇒ G(z) = 1+z+2z2+3z3+5z4+8z5+13z6+...+fnzn+... →(1)
    Now , Shift one position right and multiply by 'z' :-
    ⇒ zG(z) = z+z2+2z3+3z4+5z5+8z6+... →(2)
    Now, Shift one more position right and multiply by 'z' :-
    ⇒ z2G(z)=z2+z3+2z4+3z5+5z6+8z7+... →(3)
    Now, Add Equation(2) and Equation(3) :-
    ⇒ zG(z)+z2G(z)=z+2z2+3z3+5z4+8z5+13z6+...
    ⇒ zG(z)+z2G(z)=G(z)−1 (From(1))
    ⇒ G(z)−zG(z)−z2G(z)=1

    So,Generating Function for the given Fibonacci Series is:−
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28. Which of the following is false?

  • Option : B
  • Explanation :
    (A)
     Here 100 is constant so we can say both function are equal .
     Hence it is true.
    (B) √(logn) = O(log logn)
     growth rate of √(logn) is greater then loglogn so it is false.
    (C) If 0 < x < y then nx = O(ny) is always true.
    (D) 2n ≠ O(nk)
     if k is constant then this statement is false but here nothing is mentioned about K.
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29. The concatenation of two lists is to be performed in O(1) time. Which of the following implementations of a list should be used?

  • Option : C
  • Explanation :

    Algo for concatenation is ⇒
    {
    t1 = S1 → nxt ;
    t2 = S2 → nxt ;
    t1 → nxt = S2
    t2 → nxt = S1
    S1 → nxt = t2
    S2 → nxt = t1
    }
    it is sequential alqoni them so complexity is O(1)
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30. Let f (n) = n2 logn and g(n) = n(logn)10 be two positive functions of n. Which of the following statements is correct?

  • Option : B
  • Explanation :
    f(n) = n2 logn
    g(n) = n (logn)10
    Here we can remove common factor from both the function to simply the value of f(n) & g(n)
    So f(n) = n
    g(n) = (logn)9
    Now choose the largest value of n to compare both the function.
    if n = 2100 then f(n) = 2100
    g(n) = (100)9
    f(n) > g(n).
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