Signal, Image and Video Processing, Volume (14), No (4), Year (2019-12) , Pages (781-789)

Title : ( Decreasing Cramer–Rao lower bound by preprocessing steps )

Authors: sara monem khorasani , Ghosheh Abed Hodtani , Mohammad Molavi Kakhki ,

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Abstract

In this paper, having reviewed necessary preliminaries, including sparsity, Tsallis entropy, diversity, preprocessing, fisher information, and Cramer–Rao bound, we analyze the impact of preprocessing a signal on the signal sparsity related to Cramer–Rao lower bound and its main feature, for example, its reconstruction error. The main idea of this paper is to increase the sparsity of a vector, or to decrease its nonzero elements, then to compute the estimation error bound before and after sparsifying the signal. Finally, the claims are validated numerically. We implement Savitzky–Golay filtering on some ECG signals (applying MIT-BIH database of cardiac signals) and then compress them, to illustrate that the sparsity (the reconstruction error) of non-filtered signal was less (more) than that of filtered one. The results can be useful in signal compression and transmission procedures to have fewer recovery errors.

Keywords

Sparsity · Gini index · Estimator variance · Cramer–Rao bound (CRB) · Fisher information matrix (FIM) · Preprocessing
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@article{paperid:1077221,
author = {Monem Khorasani, Sara and Abed Hodtani, Ghosheh and Molavi Kakhki, Mohammad},
title = {Decreasing Cramer–Rao lower bound by preprocessing steps},
journal = {Signal, Image and Video Processing},
year = {2019},
volume = {14},
number = {4},
month = {December},
issn = {1863-1703},
pages = {781--789},
numpages = {8},
keywords = {Sparsity · Gini index · Estimator variance · Cramer–Rao bound (CRB) · Fisher information matrix (FIM) · Preprocessing},
}

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%0 Journal Article
%T Decreasing Cramer–Rao lower bound by preprocessing steps
%A Monem Khorasani, Sara
%A Abed Hodtani, Ghosheh
%A Molavi Kakhki, Mohammad
%J Signal, Image and Video Processing
%@ 1863-1703
%D 2019

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