BONA FIDE RIESZ PROJECTIONS FOR DENSITY ESTIMATION

被引:1
|
作者
Pla, Pol del Aguila [1 ,2 ]
Unser, Michael [2 ]
机构
[1] CIBM Ctr Biomed Imaging, Lausanne, Switzerland
[2] Ecole Polytech Fed Lausanne, Biomed Imaging Grp, Lausanne, Switzerland
关键词
Non-negativity; Riesz bases; generalized sampling; convex optimization; ARRIVAL RATE; APPROXIMATION;
D O I
10.1109/ICASSP43922.2022.9746780
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
The projection of sample measurements onto a reconstruction space represented by a basis on a regular grid is a powerful and simple approach to estimate a probability density function. In this paper, we focus on Riesz bases and propose a projection operator that, in contrast to previous works, guarantees the bona fide properties for the estimate, namely, non-negativity and total probability mass 1. Our bona fide projection is defined as a convex problem. We propose solution techniques and evaluate them. Results suggest an improved performance, specifically in circumstances prone to rippling effects.
引用
收藏
页码:5613 / 5616
页数:4
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