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Square-free words do not have adjacent repeated factors. [1] To clarify, "dining" is not square-free since "in" is repeated consecutively, while "servers" is square-free, its two "er" factors not being adjacent. Thue proves his conjecture on the existence of infinite square-free words by using substitutions. A substitution is a way to take a ...
If k > 1 the remaining elements of the k-combination form the k − 1-combination corresponding to the number () in the combinatorial number system of degree k − 1, and can therefore be found by continuing in the same way for and k − 1 instead of N and k.
In the mathematical field of graph theory, a word-representable graph is a graph that can be characterized by a word (or sequence) whose entries alternate in a prescribed way. In particular, if the vertex set of the graph is V , one should be able to choose a word w over the alphabet V such that letters a and b alternate in w if and only if the ...
Initially, k = 0. While k and m are less than N, compare S[k] (the k-th symbol of the string S) to S[m]. There are three possible outcomes: S[k] is equal to S[m]: append S[m] to the current collected symbols. Increment k and m. S[k] is less than S[m]: if we append S[m] to the current collected symbols, we'll get a Lyndon word. But we can't add ...
3 out of 4638576 [1] or out of 580717, [2] if rotations and reflections are not counted as distinct, Hamiltonian cycles on a square grid graph 8х8. Enumerative combinatorics is an area of combinatorics that deals with the number of ways that certain patterns can be formed.
The words 1, r, r 2, ..., r n-1, s, sr, ..., sr n-1 are a normal form for the dihedral group Dih n with S = {s, r} and 1 as above. The set of words of the form x m y n for m,n ∈ Z are a normal form for the direct product of the cyclic groups x and y with S = {x, y}. The set of reduced words in S are the unique normal form for the free group ...
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A word n-gram language model is a purely statistical model of language. It has been superseded by recurrent neural network–based models, which have been superseded by large language models. [1] It is based on an assumption that the probability of the next word in a sequence depends only on a fixed size window of previous words.