3 research outputs found
Finite-State Complexity and the Size of Transducers
Finite-state complexity is a variant of algorithmic information theory
obtained by replacing Turing machines with finite transducers. We consider the
state-size of transducers needed for minimal descriptions of arbitrary strings
and, as our main result, we show that the state-size hierarchy with respect to
a standard encoding is infinite. We consider also hierarchies yielded by more
general computable encodings.Comment: In Proceedings DCFS 2010, arXiv:1008.127
A linearly computable measure of string complexity
AbstractWe present a measure of string complexity, called I-complexity, computable in linear time and space. It counts the number of different substrings in a given string. The least complex strings are the runs of a single symbol, the most complex are the de Bruijn strings. Although the I-complexity of a string is not the length of any minimal description of the string, it satisfies many basic properties of classical description complexity. In particular, the number of strings with I-complexity up to a given value is bounded, and most strings of each length have high I-complexity