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Sampling, Splitting and Merging in Coinductive Stream Calculus

机译:归纳流演算中的采样,拆分和合并

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We study various operations for partitioning, projecting and merging streams of data. These operations are motivated by their use in dataflow programming and the stream processing languages. We use the framework of stream calculus and stream circuits for defining and proving properties of such operations using behavioural differential equations and coinduction proof principles. We study the invariance of certain well patterned classes of streams, namely rational and algebraic streams, under splitting and merging. Finally we show that stream circuits extended with gates for dyadic split and merge are expressive enough to realise some non-rational algebraic streams, thereby going beyond ordinary stream circuits.
机译:我们研究了各种用于分区,投影和合并数据流的操作。这些操作是由于它们在数据流编程和流处理语言中的使用而引起的。我们使用流微积分和流电路的框架,使用行为微分方程和协推证明原理来定义和证明此类操作的属性。我们研究了在分裂和合并下,某些模式良好的流类别(即有理流和代数流)的不变性。最后,我们证明了用门进行二分分割和合并扩展的流电路具有足够的表现力,可以实现一些非理性的代数流,从而超越了普通的流电路。

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