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

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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,

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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.

This paper introduces a new nonlinear filter for a discrete time, linear system which is observed in additive non-Gaussian measurement noise. The new filter is recursive, computationally efficient and has significantly improved performance over other linear and nonlinear schemes. The problem

This letter investigates the average symbol error probability (ASEP) of pulse amplitude modulation and quadrature amplitude modulation coherent signaling over flat fading channels subject to additive white generalized Gaussian noise. The new ASEP results are derived in a generic closed