Bénière et al. Vol. 25, No. 4/April 2008/J. Opt. Soc. Am. A 919 Degree of polarization estimation in the presence

analysis of a reduced

Detection of micro nucleus in human lymphocytes altered by Gaussian noise using convolution neural network

Products of Gaussian noises often emerge as the result of non-linear detection techniques or as parasitic effects, and their proper handling is important in many practical applications, including fluctuation-enhanced sensing, indoor air or environmental quality monitoring, etc. We use Rice’s random

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of photodetection noise comes from measuring the photon-flux operator. The Glauber coherent states are Gaussian quantum states which represent classical electromagnetic radiation. Quantum photodetection of these states yields statistics that are indistinguishable from the corresponding Poisson point-process results

Assuming that a stochastic process X = (Xt)t≥0 is a sum of a compound Poisson process Y = (Yt)t≥0 with known intensity λ and unknown jump size density f, and an independent Brownian motion Z = (Zt)t≥0, we consider the problem of nonparametric estimation of f from low frequency observations from X. The estimator of f is constructed via Fourier inversion and kernel smoothing. Our main result deals with asymptotic normality of the proposed estimator at a fixed point.

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Abstract—This paper considers constrained minimization methods in a unified framework for the recovery of high-dimen-sional sparse signals in three settings: noiseless, bounded error,