NONPARAMETRIC ONE-BIT QUANTIZERS FOR DISTRIBUTED ESTIMATION

被引：0

作者：

Chen, Hao ^{[1
]}

Varshney, Pramod K. ^{[1
]}

机构：

[1] Syracuse Univ, Dept EECS, Syracuse, NY 13244 USA

来源：

2008 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS, VOLS 1-6 | 2008年

关键词：

Distributed estimation; sensor networks; nonparametric distributed estimation;

D O I：

10.1109/ISIT.2008.4595028

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, we consider the distributed parameter estimation problem using one-bit quantized data from local sensors, Nonparametric distributed estimators are proposed based on knowledge of the moments of sensor noise. These estimators are shown to be either unbiased or asymptotically unbiased with bounded estimation variance for all possible parameter values. Relationship between the proposed approaches and dithering in quantization is investigated. Performance comparison is made between the proposed estimators and the Sign quantizer via an illustrative example.

引用

页码：459 / 463

页数：5

共 14 条

[1]

CHEN H, NONPARAMETRIC UNPUB

[2]

GRAY RM, 1993, IEEE T INFORM THEORY, V39, P805, DOI 10.1109/18.256489

[3] DISTRIBUTED ESTIMATION AND QUANTIZATION [J].