@inproceedings{d3aef2d49e6641858733b2bd238be7ef,
title = "Nonparametric one-bit quantizers for distributed estimation",
abstract = "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.",
keywords = "Distributed estimation, Nonparametric distributed estimation, Sensor networks",
author = "Hao Chen and Varshney, {Pramod K.}",
year = "2008",
doi = "10.1109/ISIT.2008.4595028",
language = "English (US)",
isbn = "9781424422579",
series = "IEEE International Symposium on Information Theory - Proceedings",
pages = "459--463",
booktitle = "Proceedings - 2008 IEEE International Symposium on Information Theory, ISIT 2008",
note = "2008 IEEE International Symposium on Information Theory, ISIT 2008 ; Conference date: 06-07-2008 Through 11-07-2008",
}