On the least squares estimator asymptotic normality of the multivariate symmetric textured surface parameters

IF 0.4 Q4 STATISTICS & PROBABILITY
A. Ivanov, I. Savych
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引用次数: 3

Abstract

A multivariate trigonometric regression model is considered. Various discrete modifications of the similar bivariate model received serious attention in the literature on signal and image processing due to multiple applications in the analysis of symmetric textured surfaces. In the paper asymptotic normality of the least squares estimator for amplitudes and angular frequencies is obtained in multivariate trigonometric model assuming that the random noise is a homogeneous or homogeneous and isotropic Gaussian, in particular, strongly dependent random field on  R M , M > 2. \mathbb {R}^M,\,\, M>2.
多元对称纹理曲面参数的最小二乘估计渐近正态性
考虑了一个多元三角回归模型。由于在对称纹理表面分析中的多种应用,类似的二元模型的各种离散修改在信号和图像处理的文献中受到了重视。本文在多元三角模型中,假设随机噪声是齐次或齐次各向同性高斯,特别是R M,M>2上的强相关随机场,得到了振幅和角频率的最小二乘估计的渐近正态性。\mathbb{R}^M,\,\,M>2。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.30
自引率
0.00%
发文量
22
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