Related papers: Forward-fitting STIX visibilities
This article introduces an enhanced particle swarm optimizer (PSO), termed Orthogonal PSO with Mutation (OPSO-m). Initially, it proposes an orthogonal array-based learning approach to cultivate an improved initial swarm for PSO,…
context: The combination of image restoration and a Fabry-P\'{e}rot interferometer (FPI) based instrument in solar observations results in specific calibration issues. FPIs generally show variations over the field-of-view, while in the…
Modern Giant Segmented Mirror Telescopes (GSMTs) like the Extremely Large Telescope, which is currently under construction, depend heavily on Adaptive Optics (AO) systems to correct for atmospheric distortions. However, a residual blur…
Stochastic Multi-Objective Optimization (SMOO) is critical for decision-making trading off multiple potentially conflicting objectives in uncertain environments. SMOO aims at identifying the Pareto frontier, which contains all mutually…
We consider stochastic convex optimization problems with affine constraints and develop several methods using either primal or dual approach to solve it. In the primal case, we use a special penalization technique to make the initial…
This paper proposes the application of particle swarm optimization (PSO) to the problem of finite element model (FEM) selection. This problem arises when a choice of the best model for a system has to be made from set of competing models,…
Massive stars play a critical role in the evolution of galaxies, but their formation remains poorly understood. One challenge is accurate measurement of the physical properties of massive protostars, such as current stellar mass, envelope…
Context: Characterization of instrumental effects in astronomical imaging is important in order to extract accurate physical information from the observations. The measured image in a real optical instrument is usually represented by the…
CLEAN is a well-established deconvolution approach to Fourier imaging at both radio wavelwengths and hard X-ray energies. However, specifically for hard X-ray imaging, CLEAN suffers two significant drawbacks: a rather limited degree of…
Computing proposed exact $G$-optimal designs for response surface models is a difficult computation that has received incremental improvements via algorithm development in the last two-decades. These optimal designs have not been considered…
Compressed sensing has shown great potentials in accelerating magnetic resonance imaging. Fast image reconstruction and high image quality are two main issues faced by this new technology. It has been shown that, redundant image…
Initially designed to detect and characterize exoplanets, extreme adaptive optics systems (AO) open a new window on the solar system by resolving its small bodies. Nonetheless, despite the always increasing performances of AO systems, the…
Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems which cannot be solved…
Aims: The aim of this work is to develop a method to systematically detect and characterise fast-time variations ($\gtrsim 1$s) in the non-thermal hard X-ray (HXR) time profiles of solar flares using high-resolution data from Solar…
In x-ray microscopy, traditional raster-scanning techniques are used to acquire a microscopic image in a series of step-scans. Alternatively, scanning the x-ray probe along a continuous path, called a fly-scan, reduces scan time and…
Radial velocity instruments require high spectral resolution and extreme thermo-mecanical stability, even more difficult to achieve in near-infra red (NIR) where the spectrograph has to be cooled down. For a seeing-limited spectrograph, the…
Estimating shape and appearance of a three dimensional object from a given set of images is a classic research topic that is still actively pursued. Among the various techniques available, PS is distinguished by the assumption that the…
This paper presents a novel approach to Visual Inertial Odometry (VIO), focusing on the initialization and feature matching modules. Existing methods for initialization often suffer from either poor stability in visual Structure from Motion…
Pose graph optimization (PGO) is a well-known technique for solving the pose-based simultaneous localization and mapping (SLAM) problem. In this paper, we represent the rotation and translation by a unit quaternion and a three-dimensional…
The key to accurate 3D shape measurement in Fringe Projection Profilometry (FPP) is the proper calibration of the measurement system. Current calibration techniques rely on phase-coordinate mapping (PCM) or back-projection stereo-vision…