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An information-lossless decomposition theory of relational information systems

机译:关系信息系统的无损信息分解理论

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Relational information systems, systems that can be represented by tables of finite states, are commonly used in many areas such as logic circuits, finite-state machines, and relational databases. Decomposition is a natural method of handling complex systems and removing redundancies. It splits a table into a network of smaller, simpler, and interrelated new tables. In order to preserve the original features of the system, any valid decomposition must be lossless. Commutative partitions play an important role in the decomposition. The commutative property is essentially a general algebraic formulation of independency of two partitions. We express the interdependency of two commutative partitions by a bipartite graph, and classify the hierarchical independency structures by the topological property of bipartite graphs. In particular, we show that two partitions are decomposable, the strongest version of dependency, if and only if the associate bipartite graph is uniform. We also adopt Shannon's entropy to quantify the amount of information contained in each partition, and formulate the information-lossless decomposition by the entropy conservation identity. Under the assumption of running intersection property, we show that the general formulation of information-lossless decomposition of relational systems is given by the entropy inclusion-exclusion equality. Applications of these formulations to Boolean logic circuits and relational databases are presented to manifest the information-lossless decomposition processes.
机译:关系信息系统是可以用有限状态表表示的系统,通常用于许多领域,例如逻辑电路,有限状态机和关系数据库。分解是处理复杂系统并消除冗余的自然方法。它将表拆分为更小,更简单且相互关联的新表的网络。为了保留系统的原始功能,任何有效的分解都必须是无损的。可交换分区在分解中起重要作用。交换性质本质上是两个分区的独立性的一般代数形式。我们通过二分图表示两个交换分区的相互依赖性,并通过二分图的拓扑性质对层次独立结构进行分类。特别是,当且仅当关联二部图是一致的时,我们证明两个分区是可分解的,是依赖性的最强版本。我们还采用Shannon熵来量化每个分区中包含的信息量,并通过熵守恒恒等式来表达无损信息分解。在运行相交性质的假设下,我们表明关系系统的信息无损分解的一般公式是由熵包含-排除等式给出的。介绍了这些公式在布尔逻辑电路和关系数据库中的应用,以证明信息无损分解过程。

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