Answer:
-26
Explanation:
The given binary number is 1110 0101. Also given that the signed binary number is represented using one's compliment.
We begin by computing the 1s complement representation of 1110 0101 by inverting the bits: 00011010
Converting 00011010 to decimal, it corresponds to 26.
So the 1s complement of the original number is 26. This means that the original number was -26.
Answer: Question 1 is A Question 2 is C
Explanation:
Answer:
(a) someFunc(3) will be called 4 times.
(b) For non negative number n someFunc method calculates 2^2^n.
Explanation:
When you call someFunc(5) it will call someFunc(4) two time.
So now we have two someFunc(4) now each someFunc(4) will call someFunc(3) two times.Hence the call to someFun(3) is 4 times.
someFunc(n) calculates someFunc(n-1) two times and calculates it's product.
someFunc(n) = someFunc(n-1)^2..........(1)
someFunc(n-1)=someFunc(n-2)^2..........(2)
substituting the value form eq2 to eq 1.
someFunc(n)=someFunc(n-2)^2^2
.
.
.
.
= someFunc(n-n)^2^n.
=2^2^n
2 raised to the power 2 raised to the power n.
Answer: True
Explanation:
Subset sum problem and Knapsack problem can be solved using dynamic programming.
In case of Knapsack problem there is a set of weights associative with objects and a set of profits associated with each object and a total capacity of knapsack let say C. With the help of dynamic programming we try to include object's weight such that total profit is maximized without fragmenting any weight of objects and without exceeding the capacity of knapsack, it is also called as 0/1 knapsack problem.
Similar to knapsack problem, in subset sum problem there is set of items and a set of weights associated with the items and a capacity let say C, task is to choose the subset of items such that total sum of weights associated with items of subset is maximized without exceeding the total capacity.
On the basis of above statements we can say that subset sum problem is generalization of knapsack problem.
