This is my assignment question: Explain with an开发者_如何学运维 example quick sort , merge sort and heap sort .
for i := 1 to n do j := 2; while j < i do j := j^4; I\'m really confused when it comes to Big-O notation, so I\'d like to know if it\'s O(n log n). That\'s my gut, but I can\'t prove it. I know t
As a thought exercise, I am trying to think of an algor开发者_Python百科ithm which has a non-monotonic complexity curve. The only thing I could think of was some algorithm with asymptotic solution in
I\'m looking for a algorithm that can compute an approximation of the Kolmogorov complexity of given input string.So if K is the Kolmogorov complexity of a st开发者_运维技巧ring S, and t represents ti
I\'m just learning Haskell, so sorry if my question is stupid. I\'m reading learnyouahaskell.com and now I\'m at chapter 5 \"Recursion\". There\'s an example of im开发者_StackOverflow中文版plementatio
I\'d like to under开发者_JAVA技巧stand how to efficiently estimate hardware requirements for certain complex algorithms using some well known heuristic approach.
What is the best way of comparing code complexity of functional language a开发者_如何转开发nd imperative language?
See: http://kks.cabal.fi/GoodEnoughSearch I have gone through quite many papers and sites. I have not found where this algorithm has been presented before, or that someone has made something similar,
Please, help me to compare complexity of two algorithms. O(N+1000) + O(M*log(M)) O(N*5) + O(2000) N = 100000
What is the technical definition of theoretical computer science?(Or, what should it be?) What main 开发者_如何学Csubfields does it include, and what is the commonality that separates them from the r
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