Quadratic estimation of multivariate signals from randomly delayed measurements

被引：14

作者：

Nakamori, S

Hermoso-Carazo, A

Linares-Pérez, J

机构：

[1] Kagoshima Univ, Fac Educ, Dept Technol, Kagoshima 8900065, Japan

[2] Univ Granada, Dpto Estadist & IO, Granada, Spain

来源：

MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING | 2005年 / 16卷 / 04期

关键词：

multivariate signal estimation; least-squares; delayed measurement;

D O I：

10.1007/s11045-005-4127-2

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper discusses the least-squares quadratic estimation problem of a multivariate discrete signal, from noisy measurements which can be delayed by one sampling period. The delay in the observations is assumed to be random and the probability of a delay in each measurement is known. The quadratic recursive estimation algorithm, which uses only the delay probabilities and the moments (up to fourth-order) of the signal and noise-measurement, is derived from a linear estimation algorithm for a suitably defined augmented system.

引用

页码：417 / 438

页数：22

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