Searched for: author:"Verhaegen, M.H.G."
(1 - 20 of 34)

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Pozzi, P. (author), Maddalena, L. (author), Ceffa, N.G. (author), Soloviev, O.A. (author), Vdovin, Gleb (author), Carroll, E.C.M. (author), Verhaegen, M.H.G. (author)
The use of spatial light modulators to project computer generated holograms is a common strategy for optogenetic stimulation of multiple structures of interest within a three-dimensional volume. A common requirement when addressing multiple targets sparsely distributed in three dimensions is the generation of a points cloud, focusing excitation...
journal article 2019
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Doelman, R. (author), Verhaegen, M.H.G. (author)
A rank-constrained reformulation of the blind deconvolution problem on images taken with coherent illumination is proposed. Since in the reformulation the rank constraint is imposed on a matrix that is affine in the decision variables, we propose a novel convex heuristic for the blind deconvolution problem. The proposed heuristic allows for...
journal article 2019
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Doelman, R. (author), Klingspor, Måns (author), Hansson, Anders (author), Löfberg, Johan (author), Verhaegen, M.H.G. (author)
To optimally compensate for time-varying phase aberrations with adaptive optics, a model of the dynamics of the aberrations is required to predict the phase aberration at the next time step. We model the time-varying behavior of a phase aberration, expressed in Zernike modes, by assuming that the temporal dynamics of the Zernike coefficients...
journal article 2019
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Piscaer, P.J. (author), Gupta, A. (author), Soloviev, O.A. (author), Verhaegen, M.H.G. (author)
In this paper, we propose the use of Gaussian radial basis functions (GRBFs) to model the generalized pupil function for phase retrieval. The selection of the GRBF hyper-parameters is analyzed to achieve an increased accuracy of approximation. The performance of the GRBF-based method is compared in a simulation study with another modal-based...
journal article 2018
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Monchen, Guido (author), Sinquin, B. (author), Verhaegen, M.H.G. (author)
This brief presents an algorithm for the recursive identification of Vector AutoRegressive (VAR) models of large dimensions. We consider a VAR model where the coefficient matrices can be written as a sum of Kronecker products. The algorithm proposed consists of recursively updating the Kronecker factor matrices at each new time step using...
journal article 2018
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Kazasidis, Orestis (author), Verpoort, Sven (author), Soloviev, O.A. (author), Vdovine, G.V. (author), Verhaegen, M.H.G. (author), Wittrock, Ulrich (author)
With a view to the next generation of large space telescopes, we investigate guide-starfree, image-based aberration correction using a unimorph deformable mirror in a plane conjugate to the primary mirror.We designed and built a high-resolution imaging testbed to evaluate control algorithms. In this paper we use an algorithm based on the...
journal article 2018
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Pozzi, P. (author), Soloviev, O.A. (author), Wilding, D. (author), Vdovine, G.V. (author), Verhaegen, M.H.G. (author)
We report on a universal sample-independent sensorless adaptive optics method, based on modal optimization of the second moment of the fluorescence emission from a point-like excitation. Our method employs a sample-independent precalibration, performed only once for the particular system, to establish the direct relation between the image...
journal article 2018
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Wilding, D. (author), Pozzi, P. (author), Soloviev, O.A. (author), Vdovine, G.V. (author), Verhaegen, M.H.G. (author)
Three-dimensional microscopy suffers from sample-induced aberrations that reduce the resolution and lead to misinterpretations of the object distribution. In this paper, the resolution of a three-dimensional fluorescent microscope is significantly improved by introducing an amplitude diversity in the form of a binary amplitude mask positioned...
journal article 2018
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Agbana, T.E. (author), Diehl, J.C. (author), van Pul, Fiona (author), Khan, Shahid M. (author), Patlan, Vsevolod (author), Verhaegen, M.H.G. (author), Vdovine, G.V. (author)
We have optimized the design and imaging procedures, to clearly resolve the malaria parasite in Giemsa-stained thin blood smears, using simple low-cost cellphone-based microscopy with oil immersion. The microscope uses a glass ball as the objective and the phone camera as the tube lens. Our optimization includes the optimal choice of the ball...
journal article 2018
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Gunes, B. (author), van Wingerden, J.W. (author), Verhaegen, M.H.G. (author)
In this paper, we present a novel multiple input multiple output (MIMO) linear parameter varying (LPV) state-space refinement system identification algorithm that uses tensor networks. Its novelty mainly lies in representing the LPV sub-Markov parameters, data and state-revealing matrix condensely and in exact manner using specific tensor...
journal article 2018
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Wan, Yiming (author), Keviczky, T. (author), Verhaegen, M.H.G. (author)
journal article 2017
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Agbana, T.E. (author), Gong, H. (author), Amoah, A.S. (author), Bezzubik, V (author), Verhaegen, M.H.G. (author), Vdovine, G.V. (author)
journal article 2017
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Wilding, D. (author), Soloviev, O.A. (author), Pozzi, P. (author), Vdovine, G.V. (author), Verhaegen, M.H.G. (author)
A methodology for retrieving the unknown object distribution and point-spread functions (PSFs) from a set of images acquired in the presence of temporal phase aberrations is presented in this paper. The method works by finding optimal complimentary linear filters for multi-frame deconvolution. The algorithm uses undemanding computational...
journal article 2017
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Gong, H. (author), Soloviev, O.A. (author), Verhaegen, M.H.G. (author), Vdovine, G.V. (author)
We present a quantitative phase imaging microscope based on a Shack-Hartmann sensor, that directly reconstructs the optical path difference (OPD) in reflective mode. Comparing with the holographic or interferometric methods, the SH technique needs no reference beam in the setup, which simplifies the system. With a preregistered reference, the...
journal article 2017
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Yu, C. (author), Verhaegen, M.H.G. (author)
Abstract:<br/>This note studies the identification of individual systems operating in a large-scale distributed network by considering the interconnection signals between neighboring systems to be unmeasurable. The unmeasurable interconnections act as unknown system inputs to the individual systems in a network, which poses a challenge for the...
journal article 2017
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Gunes, B. (author), van Wingerden, J.W. (author), Verhaegen, M.H.G. (author)
The major bottleneck in state-of-the-art Linear Parameter Varying (LPV) subspace methods is the curse-of-dimensionality during the first regression step. In this paper, the origin of the curse-of-dimensionality is pinpointed and subsequently a novel method is proposed which does not suffer from this bottleneck. The problem is related to the...
journal article 2017
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Yu, C. (author), Verhaegen, M.H.G. (author)
This note studies the identification of a network comprised of interconnected clusters of LTI systems. Each cluster consists of homogeneous dynamical systems, and its interconnections with the rest of the network are unmeasurable. A subspace identification method is proposed for identifying a single cluster using only local input and output data...
journal article 2017
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Doelman, R. (author), Verhaegen, M.H.G. (author)
We analyse the very general class of uncertain systems that have Linear Fractional Representations (LFRs), and uncertainty blocks in a convex set with a finite number of vertices. For these systems we design static output feedback controllers. In the general case, computing a robust static output feedback controller with optimal performance...
journal article 2017
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Verhaegen, M.H.G. (author), Hansson, A (author)
The identification of multivariable state space models in innovation form is solved in a subspace identification framework using convex nuclear norm optimization. The convex optimization approach allows to include constraints on the unknown matrices in the data-equation characterizing subspace identification methods, such as the lower triangular...
journal article 2016
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Yu, C. (author), Verhaegen, M.H.G. (author)
In this paper, we study the deterministic blind identification of multiple channel state-space models having a common unknown input using measured output signals that are perturbed by additive white noise sequences. Different from traditional blind identification problems, the considered system is an autoregressive system rather than an FIR...
journal article 2016
Searched for: author:"Verhaegen, M.H.G."
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