algorithm

问题 I have to write a program that given n , target and max , returns all the number combinations of size n that sums to target , where no number can be greater than max Example: target = 3 max = 1 n = 4 Output: [0, 1, 1, 1] [1, 0, 1, 1] [1, 1, 0, 1] [1, 1, 1, 0] It is a very simple example, but there can be a very large set of possible combinations for a more complex case. I'm looking for any algorithmic clue, but a Java implementation would be perfect. 回答1: Here a java version: import java.util

问题 I have to write a program that given n , target and max , returns all the number combinations of size n that sums to target , where no number can be greater than max Example: target = 3 max = 1 n = 4 Output: [0, 1, 1, 1] [1, 0, 1, 1] [1, 1, 0, 1] [1, 1, 1, 0] It is a very simple example, but there can be a very large set of possible combinations for a more complex case. I'm looking for any algorithmic clue, but a Java implementation would be perfect. 回答1: Here a java version: import java.util

问题 The shortest job first algorithm is shown in the following image: If it is shortest job first/shortest process next, shouldn't the order be: P1 → P5 → P3 → P4 → P2 ? Since that's the order of lowest to highest service times. Why does process 2 come second? I know if we use burst times instead, that would be the order, but I have no idea what the differences between service time and burst times are. Any help would be much appreciated explaining that graphic. 回答1: The image in the question

问题 enter image description here “⊕” is the bitwise XOR operation. I think Karatsuba’s algorithm may be used to solve the problem, but when I try to use XOR instead of "+" in the Karatsuba’s algorithm, it is tough to get the sub-problem. 回答1: The convolution theorem gives you F(C) = F(A) . F(B) where F is a Fourier-related transform, in this case the Hadamard transform, and . is point-wise multiplication. Using the fast Walsh–Hadamard transform, you can compute F(A) , F(B) , and finally C (using

问题 I am given k sorted arrays and need to merge them into one sorted array. We are assuming that n is the total number of elements in all the input arrays and that k=3. public class Merge { // Create a mergeklists() to merge 3 sorted arrays into one sorted array // Input: 3 sorted arrays a1[], a2[], a3[] // Output: one sorted array a[] that contains all the elements from input arrays public static void merge3lists(int[] a1, int[] a2, int[] a3, int[] a) { int i=0; int j=0; int h=0; int n = a1

问题 I was given this sorting function in the best answer to a question I posted. It worked on the example data, but does not appear to work on my actual data and I am not sure why. My data can be see here: JSON It's an object of objects like this: "Montana": { "superiors": [ "Massachusetts", "Oklahoma", "New Mexico" ], "inferiors": [ "North Carolina" ] } It exists to instruct the sorting function. Here, Montana must be higher up in the list than North Carolina . But below Massachusetts , Oklahoma

问题 I am trying to create a Huffman tree and i am bit confused by reading several links on internet. Some add the greater(in terms of weight) child nodes in left or some on right. So my question: (1)Is it really a matter that where to add the nodes(in left or right) ? (2) May i add node with greater weight in right or lower weight in Left ? Thanks for the help. 回答1: As long as you're consistent, it makes no difference. Either you put all the lower weights on left children and all the higher

问题 I am trying to create a Huffman tree and i am bit confused by reading several links on internet. Some add the greater(in terms of weight) child nodes in left or some on right. So my question: (1)Is it really a matter that where to add the nodes(in left or right) ? (2) May i add node with greater weight in right or lower weight in Left ? Thanks for the help. 回答1: As long as you're consistent, it makes no difference. Either you put all the lower weights on left children and all the higher

问题 I have a lot of music and i want to rank them from least favorite to favorite (this will take many days). I would like to compare two music files at a time (2-way comparison). I saw some questions on algorithms with the fewest comparisons. But the catch is that (since it's a long process) i want to add new music to the collection and in that case i don't want to start over sorting everything (thus creating a lot more comparison steps). Which algorithm has the least amount of comparisons while

问题 Given a string of digits, count the number of subwords (consistent subsequences) that are anagrams of any palindrome. My attempt in Python: def ispalin(s): if len(s)%2==0: for i in s: if s.count(i)%2!=0: return False else: sum =0 for i in set(s): if s.count(i)%2==1: sum = sum+1 if sum == 1: return True else: return False return True def solution(S): # write your code in Python 3.6 count=len(S) for i in range(len(S)): for j in range(i+1,len(S)): if ispalin(S[i:j+1]): count=count+1 return count