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Algorithms for verification of characteristic sets of discrete autonomous nD systems with n ≥ 2

机译:用于验证N≥2的离散自主ND系统特征集的算法

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An important question for multidimensional systems is to characterize the minimum information required to uniquely specify a 'trajectory'. For a discrete nD system described by partial difference equations with real constant coefficients, the notion of a characteristic set formalizes this idea. The issue of characteristic sets for n ≥ 3 has largely remained open since Valcher's seminal work for n = 2 (Valcher (2000)). In this paper, we provide a necessary and sufficient condition for a given subset (either a cone or a sub-lattice) in Z~n to be a characteristic set for a discrete scalar autonomous nD system. This necessary and sufficient condition enables us to formulate an algebraic test for verifying whether a given cone or a sub-lattice is a characteristic set for a given discrete scalar autonomous nD system. We then provide algorithms - that are implementable using standard computational algebra packages - for doing this check. This is achieved by first converting the above-mentioned necessary and sufficient condition to another equivalent algebraic condition that is more suited for applying Grobner bases theory. We further pursue the question of 'minimality' of characteristic sets. We show how the idea of minimal characteristic sub-lattices is related with the notion of autonomy degree and Krull dimension. Thus, we provide a complete solution to the problem of determining if a given cone or a sub-lattice is a characteristic set for a scalar autonomous discrete nD system.
机译:多维系统的一个重要的问题是表征唯一的指定一个“轨迹”必需的信息。用于通过与实常数系数局部差分方程描述的离散ND系统,特征集的概念形式化这种想法。特征集当n≥3的问题已经在很大程度上仍然是因为Valcher对开创性工作打开N = 2(Valcher(2000))。在本文中,我们提供一种用于沿Z〜n的成为离散标量自主ND系统特有的一组给定的子集(或圆锥体或亚晶格)的必要和充分条件。这充分必要条件,使我们制定的代数用于检验一个给定的圆锥体或子格是否是一个给定的离散标量自治第二系统特有的一组。然后,我们提供的算法 - 做此检查 - 使用标准计算代数软件包是可实现的。这是通过首先将上述的充分必要条件转换为另一种等效的代数条件更适合用于施加Grobner基理论来实现的。我们进一步追求的特性集“极小”的问题。我们将展示如何最小特征的子格的思想与自主程度和克鲁尔维数的概念有关。因此,我们提供给确定是否一个给定的锥形或亚晶格为标量自治离散ND系统的特征集的问题的完整解决方案。

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