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Computability on the probability measures on the Borel sets of the unit interval

机译:关于单位区间的Borel集上的概率测度的可计算性

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摘要

While computability theory on many countable sets is well established and for computability on the real numbers several (mutually non-equivalent) definitions are applied, for most other uncountable sets, in particular for measures, no generally accepted computability concepts at all have been available until now. It this contribution we introduce computability on the set M of probability measures on the Borel subsets of the unit interval [0,1]. Its main purpose is to demonstrate that this concept of computability is not merely an ad hoc definition but has very natural properties. Although the definitions and many results can of course be transferred to more general spaces of measures, we restrict our attention to M in order to keep the technical details simple and concentrate on the central ideas. In particular, we show that simple obvious requirements exclude a number of similar definitions, that the definition leads to the expected computability results, that there are other natural definitions inducing the same computability theory and that the theory is embedded smoothly into classical measure theory. As background we consider TTE, Type 2 Theory of Effectivity [10, 11, 19], which provides a frame for very realistic computability definitions. In this approach, computability is defined on finite and infinite sequences of symbols explicitly by Turing machines and on other sets by means of notations and representations. Canonical representations are derived from computation spaces [18]. We introduce a standard representation #delta#_m:is contained in=#SIGMA#~(#omega#)->M via some natural computation space defined by a subbase #sigma# (the atomic properties) of some topology #tau# on M and a standard notation of #sigma#. While several modifications of #delta#_m suggesting themselves at first glance, violate simple and obvious requirements, #delta#_m has several very natural properties and hence should induce an important computability theory, Many interesting functions on measures turn out to be computable, in particular linear combination, integration of continuous functions and any transformation defined by a computable iterated function system with probabilities. Some other natural representations of M are introduced, among them a Cauchy representation associated with the Hutchinson metric, and proved to be equivalent to #delta#_m. As a corollary, the final topology #tau# of #delta#_m is the well-known weak topology on M.
机译:虽然已经很好地建立了许多可数集的可计算性理论,并且对于实数上的可计算性,应用了几个(互不等价的)定义,但是对于大多数其他不可数集,尤其是度量,直到现在,才有公认的可计算性概念现在。正是由于这一贡献,我们才对单位间隔[0,1]的Borel子集上的概率度量集M引入了可计算性。其主要目的是证明可计算性的概念不仅是临时定义,而且具有非常自然的特性。尽管当然可以将定义和许多结果转移到更广泛的度量空间,但是我们将注意力集中在M上,以使技术细节保持简单并集中于中心思想。特别是,我们表明简单的明显要求排除了许多相似的定义,该定义导致了预期的可计算性结果,还有其他自然定义引发了相同的可计算性理论,并且该理论被平滑地嵌入了经典测度理论中。作为背景,我们考虑了TTE,即有效性的类型2理论[10,11,19],它为非常现实的可计算性定义提供了框架。在这种方法中,图灵机显式地在符号的有限和无限序列上定义可计算性,而在其他集合上通过符号和表示法定义可计算性。规范表示是从计算空间得出的[18]。我们引入标准表示形式#delta#_m:包含在=#SIGMA#〜(#omega#)-> M中,这是通过某些拓扑#tau#的子碱基#sigma#(原子性质)定义的自然计算空间来完成的M和标准符号#sigma#。尽管#delta#_m的几种修改乍看起来表明它们违反了简单而明显的要求,但#delta#_m具有几个非常自然的特性,因此应该引出一个重要的可计算性理论。特定的线性组合,连续函数的集成以及由具有概率的可计算迭代函数系统定义的任何变换。引入了M的其他一些自然表示形式,其中包括与Hutchinson度量相关的柯西表示形式,并证明等效于#delta#_m。因此,#delta#_m的最终拓扑#tau#是M上众所周知的弱拓扑。

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