Search results for "Inverse"
showing 10 items of 630 documents
Multilevel preconditioning and adaptive sparse solution of inverse problems
2012
Derivatives and inverse of a linear-nonlinear multi-layer spatial vision model
2016
Linear-nonlinear transforms are interesting in vision science because they are key in modeling a number of perceptual experiences such as color, motion or spatial texture. Here we first show that a number of issues in vision may be addressed through an analytic expression of the Jacobian of these linear-nonlinear transforms. The particular model analyzed afterwards (an extension of [Malo & Simoncelli SPIE 2015]) is illustrative because it consists of a cascade of standard linear-nonlinear modules. Each module roughly corresponds to a known psychophysical mechanism: (1) linear spectral integration and nonlinear brightness-from-luminance computation, (2) linear pooling of local brightness…
Optimal nonlinear damping control of second-order systems
2020
Novel nonlinear damping control is proposed for the second-order systems. The proportional output feedback is combined with the damping term which is quadratic to the output derivative and inverse to the set-point distance. The global stability, passivity property, and convergence time and accuracy are demonstrated. Also the control saturation case is explicitly analyzed. The suggested nonlinear damping is denoted as optimal since requiring no design additional parameters and ensuring a fast convergence, without transient overshoots for a non-saturated and one transient overshoot for a saturated control configuration.
Efficient Parallel Nash Genetic Algorithm for Solving Inverse Problems in Structural Engineering
2015
A parallel implementation of a game-theory based Nash Genetic Algorithm (Nash-GAs) is presented in this paper for solving reconstruction inverse problems in structural engineering. We compare it with the standard panmictic genetic algorithm in a HPC environment with up to eight processors. The procedure performance is evaluated on a fifty-five bar sized test case of discrete real cross-section types structural frame. Numerical results obtained on this application show a significant achieved increase of performance using the parallel Nash-GAs approach compared to the standard GAs or Parallel GAs.
Nonlinear Pulse Shaping in Optical Fibres with a Neural Network
2020
We use a supervised machine-learning model based on a neural network to solve the direct and inverse problems relating to the shaping of optical pulses that occurs upon nonlinear propagation in optical fibres.
Kinematic calibration method for a 5-DOF Gantry-Tau parallel kinematic machine
2013
In this paper a new step-wise approach to kinematic calibration of a 5-DOF Gantry-Tau parallel kinematic machine (PKM) is presented. The approach can be adapted to the modular design of the PKM and the calibration could easily perform part of the assembly instructions for the machine. By using measurements from a laser tracker and least-squares estimates of polynomial functions, a typical accuracy of about 20 micrometer was achieved for the base actuators. The remaining set of 30 general parameters for the hexapod link structure and spherical joint connections were successfully estimated using the Complex search-based evolutionary algorithm.
A Meshfree Solver for the MEG Forward Problem
2015
Noninvasive estimation of brain activity via magnetoencephalography (MEG) involves an inverse problem whose solution requires an accurate and fast forward solver. To this end, we propose the Method of Fundamental Solutions (MFS) as a meshfree alternative to the Boundary Element Method (BEM). The solution of the MEG forward problem is obtained, via the Method of Particular Solutions (MPS), by numerically solving a boundary value problem for the electric scalar potential, derived from the quasi-stationary approximation of Maxwell’s equations. The magnetic field is then computed by the Biot-Savart law. Numerical experiments have been carried out in a realistic single-shell head geometry. The p…
Total Variation Regularization in Digital Breast Tomosynthesis
2013
We developed an iterative algebraic algorithm for the reconstruction of 3D volumes from limited-angle breast projection images. Algebraic reconstruction is accelerated using the graphics processing unit. We varied a total variation (TV)-norm parameter in order to verify the influence of TV regularization on the representation of small structures in the reconstructions. The Barzilai-Borwein algorithm is used to solve the inverse reconstruction problem. The quality of our reconstructions was evaluated with the Quart Mam/Digi Phantom, which features so-called Landolt ring structures to verify perceptibility limits. The evaluation of the reconstructions was done with an automatic LR detection a…
Combining Biophysical Modeling and Machine Learning to Predict Location of Atrial Ectopic Triggers
2018
The search for focal ectopic activity in the atria triggered from non-standard regions can be time consuming. The use of body surface potential maps to plan the intervention can be helpful, but require an advance processing of the data, that usually involves to solve an ill-posed inverse problem. In addition, changes in maps due to pathological substrate such as fibrosis might affect the expected electrical patterns. In this work, we use a machine learning approach to relate ectopic focus activity in different atrial regions with body surface potential maps, and consider the effects of fibrosis in various densities and distributions. Results show that as fibrosis increases over 15% the syst…
Spin transport in multilayer systems with fully epitaxial NiO thin films
2018
We report the generation and transport of thermal spin currents in fully epitaxial $\ensuremath{\gamma}\text{\ensuremath{-}}\mathrm{F}{\mathrm{e}}_{2}{\mathrm{O}}_{3}/\mathrm{NiO}(001)/\mathrm{Pt}$ and $\mathrm{F}{\mathrm{e}}_{3}{\mathrm{O}}_{4}/\mathrm{NiO}(001)/\mathrm{Pt}$ trilayers. A thermal gradient, perpendicular to the plane of the sample, generates a magnonic spin current in the ferrimagnetic maghemite $(\ensuremath{\gamma}\text{\ensuremath{-}}\mathrm{F}{\mathrm{e}}_{2}{\mathrm{O}}_{3})$ and magnetite $(\mathrm{F}{\mathrm{e}}_{3}{\mathrm{O}}_{4})$ thin films by means of the spin Seebeck effect. The spin current propagates across the epitaxial, antiferromagnetic insulating NiO layer…