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- W2169074448 abstract "In this paper, we present two density estimation methods based on constrained expectation-maximization (EM) algorithm. We propose a penalty-based maximum-entropy expectation-maximization (MEEM) algorithm to obtain a smooth estimate of the density function. We further propose an attraction-repulsion expectation-maximization (AREM) algorithm for density estimation in order to determine equilibrium between over-smoothing and over-fitting of the estimated density function. Computer simulation results are used to show the effectiveness of the proposed constrained expectation-maximization algorithms in image reconstruction and sensor field estimation from randomly scattered samples." @default.
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- W2169074448 date "2008-03-01" @default.
- W2169074448 modified "2023-10-16" @default.
- W2169074448 title "A new approach to constrained expectation-maximization for density estimation" @default.
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- W2169074448 doi "https://doi.org/10.1109/icassp.2008.4518453" @default.
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