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• W4224949960 abstract "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." @default.
• W4224949960 created "2022-04-28" @default.
• W4224949960 creator A5027830035 @default.
• W4224949960 creator A5050615336 @default.
• W4224949960 date "2022-05-23" @default.
• W4224949960 modified "2023-10-16" @default.
• W4224949960 title "Bona Fide Riesz Projections for Density Estimation" @default.
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• W4224949960 doi "https://doi.org/10.1109/icassp43922.2022.9746780" @default.
• W4224949960 hasPublicationYear "2022" @default.
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