具有有限记忆的图灵机

W. R. Oliveira, M. D. Souto, Teresa B Ludermir
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引用次数: 2

摘要

受我们早期通过神经网络研究图灵可计算性的工作(1992,2001)和Maass等人(1997,1998)关于在考虑噪声(或权重的有限精度)时神经网络实际计算的极限的结果的启发,我们引入了确定图灵机(DTM)的概念并研究了它的一些性质。我们将每个图灵机(TM)关联到一个有限状态自动机(FSA),负责下一个状态转换和动作(输出和头部运动)。DTM是指其FSA是确定的TM。如果FSA的当前状态可以由最后k个输入唯一地确定,则它是确定的(k阶>0)。我们证明了DTM的功能严格不如TM强大,但能够计算所有简单的函数。有限记忆图灵机的概念在计算上与图灵机是等价的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Turing machines with finite memory
Motivated by our earlier work on Turing computability via neural networks (1992, 2001) and the results by Maass et al. (1997, 1998) on the limit of what can be actually computed by neural networks when noise (or limited precision on the weights) is considered, we introduce the notion of definite Turing machine (DTM) and investigate some of its properties. We associate to every Turing machine (TM) a finite state automaton (FSA) responsible for the next state transition and action (output and head movement). A DTM is TM in which its FSA is definite. A FSA is definite (of order k>0) if its present state can be uniquely determined by the last k inputs. We show that DTM are strictly less powerful than TM but are capable to compute all simple functions. The corresponding notion of finite-memory Turing machine is shown to be computationally equivalent to Turing machine.
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