MMSE estimation from quantized observations in the nonasymptotic regime

This thesis studies MMSE estimation on the basis of quantized noisy observations. It presents nonasymptotic bounds on MMSE regret due to quantization for two settings: (1) estimation of a scalar random variable given a quantized vector of n conditionally independent observations, and (2) estimation of a p-dimensional random vector given a quantized vector of n observations (not necessarily independent) when the full MMSE estimator has a sub-Gaussian concentration property.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2016

Author dc:creator

• Lee, Jaeho

Contributors dc:contributor

• Raginsky, Maxim

• functional quantization
• nonasymptotic bounds

Statement dc:rights

• Copyright 2015 Jaeho Lee

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/89048

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/89048