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Selection sort: Find the smallest (or biggest) element in the array, and put it in the proper place. Swap it with the value in the first position. Repeat until array is sorted. Quick sort: Partition the array into two segments. In the first segment, all elements are less than or equal to the pivot value.
Related problems include approximate sorting (sorting a sequence to within a certain amount of the correct order), partial sorting (sorting only the k smallest elements of a list, or finding the k smallest elements, but unordered) and selection (computing the kth smallest element). These can be solved inefficiently by a total sort, but more ...
The longest increasing subsequence problem is closely related to the longest common subsequence problem, which has a quadratic time dynamic programming solution: the longest increasing subsequence of a sequence is the longest common subsequence of and , where is the result of sorting.
Open a new empty bin, bin #1. For each item from largest to smallest, find the first bin into which the item fits, if any. If such a bin is found, put the new item in it. Otherwise, open a new empty bin put the new item in it. In short: FFD orders the items by descending size, and then calls first-fit bin packing. An equivalent description of ...
Typically, it is assumed that w ≥ log 2 (max(n, K)); that is, that machine words are large enough to represent an index into the sequence of input data, and also large enough to represent a single key. [2] Integer sorting algorithms are usually designed to work in either the pointer machine or random access machine models of computing. The ...
Even without knowledge that we are working in the multiplicative group of integers modulo n, we can show that a actually has an order by noting that the powers of a can only take a finite number of different values modulo n, so according to the pigeonhole principle there must be two powers, say s and t and without loss of generality s > t, such that a s ≡ a t (mod n).
Name First elements Short description OEIS Mersenne prime exponents : 2, 3, 5, 7, 13, 17, 19, 31, 61, 89, ... Primes p such that 2 p − 1 is prime.: A000043 ...
[3] 2 0: bit: 10 0: bit 1 bit – 0 or 1, false or true, Low or High (a.k.a. unibit) 1.442695 bits (log 2 e) – approximate size of a nat (a unit of information based on natural logarithms) 1.5849625 bits (log 2 3) – approximate size of a trit (a base-3 digit) 2 1: 2 bits – a crumb (a.k.a. dibit) enough to uniquely identify one base pair ...