OBJECTIVE This study examines developmental and aging trends in auditory evoked potentials (AEPs) by applying two analysis methods to a large database of healthy subjects. METHODS AEPs and reaction times were recorded from 1498 healthy subjects aged 6-86 years using an auditory oddball paradigm. AEPs were analyzed using a recently published deconvolution method and conventional component scor...

We solve blind deconvolution problems where one signal is modulated by multiple random masks using nuclear norm minimization. Theoretical analysis shows the number of masks for successful recovery scales as poly-logarithm of the problem dimension. OCIS codes: 100.1455, 100.3190.

We derive asymptotic normality of kernel type deconvolution density estimators. In particular we consider deconvolution problems where the known component of the convolution has a symmetric λ-stable distribution, 0 < λ ≤ 2. It turns out that the limit behavior changes if the exponent parameter λ passes the value one, the case of Cauchy deconvolution. AMS classification: primary 62G05; secondary...

We investigate efficient algorithmic realisations for robust deconvolution of grey-value images with known space-invariant point-spread function, with emphasis on 1D motion blur scenarios. The goal is to make deconvolution suitable as preprocessing step in automated image processing environments with tight time constraints. Candidate deconvolution methods are selected for their restoration qual...

Reflection coefficients are observed in nature to have stochastic behavior that departs significantly from the white noise model. Conventional deconvolution methods, however, assume reflectivity to be a white noise process. In this paper we analyze the deconvolution process, study the implications of the assumption of white noise, and show that the conventional operator can recover only the whi...

The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smoothed `1/`2 regularization term. As the mean of the noise in the power spectrum domain depends on its variance in the time domain, the proposed method includes a variance estimation step, which allows more rob...

Blind deconvolution is a common method for restoration of blurred text images, while binarization is employed to analyze and interpret the text semantics. In literature, these tasks are typically treated independently. This paper introduces a novel binarization driven blind deconvolution approach to couple both tasks in a common framework. The proposed method is derived as an energy minimizatio...

We propose easy-to-implement algorithms to perform blind deconvolution of nonnegative images in the presence of noise of Poisson type. Alternate minimization of a regularized Kullback-Leibler cost function is achieved via multiplicative update rules. The scheme allows to prove convergence of the iterates to a stationary point of the cost function. Numerical examples are reported to demonstrate ...