Uncountable Realtime Probabilistic Classes
Abstract
We investigate the minimum cases for realtime probabilistic machines that can define uncountably many languages with bounded error. We show that logarithmic space is enough for realtime PTMs on unary languages. On binary case, we follow the same result for double logarithmic space, which is tight. When replacing the worktape with some limited memories, we can follow uncountable results on unary languages for two counters.
Domains
Computer Science [cs]Origin | Files produced by the author(s) |
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