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Polynomial alias higher degree fuzzy transform of complex-valued functions

机译:多项式别名复数值函数的高阶模糊变换

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In this article, we propose a general approach to the computation of components of the direct higher degree fuzzy transform. Apart from the orthogonal bases of the subspaces of polynomials of weighted Hilbert spaces with respect to a generalized uniform fuzzy partition, which are used in all papers on fuzzy transform of higher degree, we admit also the non-orthogonal bases. An advantage of using non-orthogonal bases consists in the possibility of replacing orthogonal polynomials, derivation of which by the Gram-Schmidt orthogonalization process can be questionable difficult or imprecise, by suitable non-orthogonal polynomials of much simpler form. We present a simple matrix calculus and show how it can be used to introduce the components of the direct higher degree fuzzy transform. With the help of the monomial basis, we prove a convergence theorem and an approximation theorem for the higher degree fuzzy transform. The results are illustrated by examples including a comparison with standard methods. (C) 2017 Elsevier B.V. All rights reserved.
机译:在本文中,我们提出了一种直接的高次模糊变换分量计算的通用方法。除了加权Hilbert空间的多项式的子空间相对于广义均匀模糊分区的正交基(在所有关于高阶模糊变换的论文中都使用过)之外,我们还接受非正交基。使用非正交基的优点在于可以替换正交多项式,而通过简单得多的合适的非正交多项式来替代通过Gram-Schmidt正交化过程推导的正交多项式可能是困难的或不精确的。我们提出一个简单的矩阵演算,并展示如何将其用于介绍直接高次模糊变换的组成部分。借助于单项式,我们证明了高阶模糊变换的收敛性定理和逼近定理。实例说明了结果,包括与标准方法的比较。 (C)2017 Elsevier B.V.保留所有权利。

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