Results 31 to 40 of about 28,366 (229)
Blind multiuser deconvolution in fading and dispersive channels [PDF]
, 1995 An adaptive near-far resistant technique for the blind joint multiuser identification and detection in asynchronous CDMA systems is analyzed in fading and dispersive GSM channels.Peer ReviewedPostprint (published ...
Rodríguez Fonollosa, Javier +3 more
core +1 more source
Zernike integrated partial phase error reduction algorithm
Results in Optics, 2021 A modification to the error reduction algorithm is reported in this paper for determining the prescription of an imaging system in terms of Zernike polynomials.
Stephen C. Cain
doaj +1 more source
A neural network approach for the blind deconvolution of turbulent flows
, 2017 We present a single-layer feedforward artificial neural network architecture trained through a supervised learning approach for the deconvolution of flow variables from their coarse grained computations such as those encountered in large eddy simulations.
Maulik, Romit, San, Omer
core +1 more source
Blind Deconvolution of Seismic Data Using f-Divergences
Entropy, 2011 This paper proposes a new approach to the seismic blind deconvolution problem in the case of band-limited seismic data characterized by low dominant frequency and short data records, based on Csiszár’s f-divergence.
Bing Zhang, Jing-Huai Gao
doaj +1 more source
Adaptive Model for Magnetic Particle Mapping Using Magnetoelectric Sensors
Sensors, 2022 Imaging of magnetic nanoparticles (MNPs) is of great interest in the medical sciences. By using resonant magnetoelectric sensors, higher harmonic excitations of MNPs can be measured and mapped in space.
Ron-Marco Friedrich, Franz Faupel
doaj +1 more source
A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping
, 2016 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 smooth \ell_1/\ell_2 regularization term. As the mean of the noise in
Mars, Jérôme I. +3 more
core +3 more sources
Blind Ptychography via Blind Deconvolution
, 2023 arXiv admin note: text overlap with arXiv:1606.04933 by other ...
openaire +2 more sources
Blind and Non-Blind Deconvolution-Based Image Deblurring Techniques for Blurred and Noisy Image
Tikrit Journal of Engineering Sciences: Image deblurring is a common issue in low-level computer vision aiming to restore a clear image from a blurred input image. Deep learning innovations have significantly advanced the solution to this issue, and numerous deblurring networks have been ...
Shayma Wail Nourildean
doaj +1 more source
Guide star based deconvolution for imaging behind turbid media
Journal of the European Optical Society-Rapid Publications, 2018 Background If structures of interest are hidden beneath turbid layers such as biological tissues, imaging becomes challenging, even impossible. However, if the point spread function of the system is known from the presence of a guide star, application of
Jale Schneider, Christof M Aegerter
doaj +1 more source
An Efficient Method for Non-Convex Blind Deconvolution
IEEE Access, 2019 This paper considers blind deconvolution problem that to recover unknown signals fand g from their convolution signal. Non-convex optimization approach is an efficient method to get the solution, but it is a challenge to find the exact solution for a non-
Yixian Liu
doaj +1 more source