Tight bounds for the space complexity of nonregular language recognition by real-time machines

Details Tight bounds for the space complexity of nonregular language recognition by real-time machines Tight bounds for the space complexity of nonregular language recognition by real-time machines

2011-08-12

arxiv.org/abs/1108.2613v1

Computer Science

Computational Complexity

10 pages, latex

Scientific paper

We examine the minimum amounts of useful memory for real-time, as opposed to one-way, computation using several different machine models. In most cases, we are able to show that the lower bounds established using arguments about one-way machines remain tight in the real-time case. It is shown that increasing the number of stacks of real-time pushdown automata can result in exponential improvement in the total amount of space usage for nonregular language recognition.

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