Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM [PDF]
, 2014 We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known.
Se Un Parka +5 more
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IEEE Transactions on Signal Processing, 2019 We introduce a novel multichannel blind deconvolution (BD) method that extracts sparse and front-loaded impulse responses from the channel outputs, i.e., their convolutions with a single arbitrary source. A crucial feature of this formulation is that it doesn't encode support restrictions on the unknowns, unlike most prior work on BD. The indeterminacy
Pawan Bharadwaj +2 more
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Blind Single Channel Deconvolution using Nonstationary Signal Processing [PDF]
, 2003 Blind deconvolution is fundamental in signal processing applications and, in particular, the single channel case remains a challenging and formidable problem. This paper considers single channel blind deconvolution in the case where the degraded observed
Rayner, Peter J. W. +1 more
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Research on Fault Extraction Method of CYCBD Based on Seagull Optimization Algorithm
Shock and Vibration, 2021 Maximum cyclostationarity blind deconvolution (CYCBD) can recover the periodic impulses from mixed fault signals comprised by noise and periodic impulses. In recent years, blind deconvolution has been widely used in fault diagnosis.
Qianqian Zhang +4 more
doaj +1 more source
Blind deconvolution of sparse pulse sequences under a minimum distance constraint: a partially collapsed Gibbs sampler method [PDF]
, 2012 For blind deconvolution of an unknown sparse sequence convolved with an unknown pulse, a powerful Bayesian method employs the Gibbs sampler in combination with a Bernoulli–Gaussian prior modeling sparsity.
Kail, Georg +3 more
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Blind Ptychography via Blind Deconvolution
CoRR, 2023 arXiv admin note: text overlap with arXiv:1606.04933 by other ...
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Semi-blind sparse image reconstruction with application to MRFM [PDF]
, 2012 We propose a solution to the image deconvolution problem where the convolution kernel or point spread function (PSF) is assumed to be only partially known.
Hero, Alfred O. +2 more
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Blind signal deconvolution based on pulsed neuron model [PDF]
ITM Web of Conferences, 2019 In this paper, we consider the vector-matrix model of a pulsed neuron, focused on solving problems of digital signal processing. We extend the application domain of the model to the blind signal deconvolution problem.
Bondarev Vladimir
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New Lagrange Multipliers for the Blind Adaptive Deconvolution Problem Applicable for the Noisy Case
Entropy, 2016 Recently, a new blind adaptive deconvolution algorithm was proposed based on a new closed-form approximated expression for the conditional expectation (the expectation of the source input given the equalized or deconvolutional output) where the output ...
Monika Pinchas
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Source Quantitative Identification by Reference-Based Cubic Blind Deconvolution Algorithm
Chinese Journal of Mechanical Engineering, 2023 The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information. However, the separation performance depends largely on the construction of reference signals.
Xin Luo +3 more
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