Robust Kalman Filtering: Asymptotic Analysis of the Least Favorable Model

We consider a robust filtering problem where the robust filter is designed according to the least favorable model belonging to a ball about the nominal model. In this approach, the ball radius specifies the modeling error tolerance and the least favorable model is computed by performing a Riccati-like backward recursion. We show that this recursion converges provided that the tolerance is sufficiently small

A Contraction Analysis of the Convergence of Risk-Sensitive Filters

A contraction analysis of risk-sensitive Riccati equations is proposed. When the state-space model is reachable and observable, a block-update implementation of the risk-sensitive filter is used to show that the N-fold composition of the Riccati map is strictly contractive with respect to the Riemannian metric of positive definite matrices, when N is larger than the number of states. The range of values of the risk-sensitivity parameter for which the map remains contractive can be estimated a priori. It is also found that a second condition must be imposed on the risk-sensitivity parameter and on the initial error variance to ensure that the solution of the risk-sensitive Riccati equation remains positive definite at all times. The two conditions obtained can be viewed as extending to the multivariable case an earlier analysis of Whittle for the scalar case.Comment: 22 pages, 6 figure

Development and application of a unified balancing approach with multiple constraints

The development of a general analytic approach to constrained balancing that is consistent with past influence coefficient methods is described. The approach uses Lagrange multipliers to impose orbit and/or weight constraints; these constraints are combined with the least squares minimization process to provide a set of coupled equations that result in a single solution form for determining correction weights. Proper selection of constraints results in the capability to: (1) balance higher speeds without disturbing previously balanced modes, thru the use of modal trial weight sets; (2) balance off-critical speeds; and (3) balance decoupled modes by use of a single balance plane. If no constraints are imposed, this solution form reduces to the general weighted least squares influence coefficient method. A test facility used to examine the use of the general constrained balancing procedure and application of modal trial weight ratios is also described

Models of cuspy triaxial stellar systems. II. Regular orbits

In the first paper of this series we used the N--body method to build a dozen cuspy (gamma ~ 1) triaxial models of stellar systems, and we showed that they were highly stable over time intervals of the order of a Hubble time, even though they had very large fractions of chaotic orbits (more than 85 per cent in some cases). The models were grouped in four sets, each one comprising models morphologically resembling E2, E3, E4 and E5 galaxies, respectively. The three models within each set, although different, had the same global properties and were statistically equivalent. In the present paper we use frequency analysis to classify the regular orbits of those models. The bulk of those orbits are short axis tubes (SATs), with a significant fraction of long axis tubes (LATs) in the E2 models that decreases in the E3 and E4 models to become negligibly small in the E5 models. Most of the LATs in the E2 and E3 models are outer LATs, but the situation reverses in the E4 and E5 models where the few LATs are mainly inner LATs. As could be expected for cuspy models, most of the boxes are resonant orbits, i.e., boxlets. Nevertheless, only the (x, y) fishes of models E3 and E4 amount to about 10 per cent of the regular orbits, with most of the fractions of the other boxlets being of the order of 1 per cent or less.Comment: Accepted for publication in the Monthly Notices of the Royal Astronomical Societ

Understanding Dyslexia Through Personalized Large-Scale Computational Models

International audienceLearning to read is foundational for literacy development, yet many children in primary school fail to become efficient readers despite normal intelligence and schooling. This condition, referred to as developmental dyslexia, has been hypothesized to occur because of deficits in vision, attention, auditory and temporal processes, and phonology and language. Here, we used a developmentally plausible computational model of reading acquisition to investigate how the core deficits of dyslexia determined individual learning outcomes for 622 children (388 with dyslexia). We found that individual learning trajectories could be simulated on the basis of three component skills related to orthography, phonology, and vocabulary. In contrast, single-deficit models captured the means but not the distribution of reading scores, and a model with noise added to all representations could not even capture the means. These results show that heterogeneity and individual differences in dyslexia profiles can be simulated only with a personalized computational model that allows for multiple deficits

Train vs. play: Evaluating the effects of gamified and non-gamified wheelchair skills training using virtual reality

This study compares the influence of a gamified and a non-gamified virtual reality (VR) environment on wheelchair skills training. In specific, the study explores the integration of gamification elements and their influence on wheelchair driving performance in VR-based training. Twenty-two non-disabled participants volunteered for the study, of whom eleven undertook the gamified VR training, and eleven engaged in the non-gamified VR training. To measure the efficacy of the VR-based wheelchair skills training, we captured the heart rate (HR), number of joystick movements, completion time, and number of collisions. In addition, an adapted version of the Wheelchair Skills Training Program Questionnaire (WSTP-Q), the Igroup Presence Questionnaire (IPQ), and the Simulator Sickness Questionnaire (SSQ) questionnaires were administered after the VR training. The results showed no differences in wheelchair driving performance, the level of involvement, or the ratings of presence between the two environments. In contrast, the perceived cybersickness was statistically higher for the group of participants who trained in the non-gamified VR environment. Remarkably, heightened cybersickness symptoms aligned with increased HR, suggesting physiological connections. As such, while direct gamification effects on the efficacy of VR-based wheelchair skills training were not statistically significant, its potential to amplify user engagement and reduce cybersickness is evident

Computer-based attention-demanding testing unveils severe neglect in apparently intact patients

We tested a group of ten post-acute right-hemisphere damaged patients. Patients had no neglect according to paper-and-pencil cancellation tasks. They were administered computer-based single- and dual-tasks, requiring to orally name the position of appearance (e.g. left vs. right) of briefly-presented lateralized targets. Patients omitted a consistent number of contralesional targets (approximate to 40%) under the single-task condition. When required to perform a concurrent task which recruited additional attentional resources (dual-tasks), patients' awareness for contralesional hemispace was severely affected, with less than one third of contralesional targets detected (approximate to 70% of omissions). In contrast, performance for ipsilesional (right-sided) targets was close to ceiling, showing that the deficit unveiled by computer-based testing selectively affected the contralesional hemispace. We conclude that computer-based, attention-demanding tasks are strikingly more sensitive than cancellation tasks in detecting neglect, because they are relatively immune to compensatory strategies that are often deployed by post-acute patients

Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with Hybrid Beamforming

Hybrid analog and digital BeamForming (HBF) is one of the enabling transceiver technologies for millimeter Wave (mmWave) Multiple Input Multiple Output (MIMO) systems. This technology offers highly directional communication, which is able to confront the intrinsic characteristics of mmWave signal propagation. However, the small coherence time in mmWave systems, especially under mobility conditions, renders efficient Beam Management (BM) in standalone mmWave communication a very difficult task. In this paper, we consider HBF transceivers with planar antenna panels and design a multi-level beam codebook for the analog beamformer comprising flat top beams with variable widths. These beams exhibit an almost constant array gain for the whole desired angle width, thereby facilitating efficient hierarchical BM. Focusing on the uplink communication, we present a novel beam training algorithm with dynamic beam ordering, which is suitable for the stringent latency requirements of the latest mmWave standard discussions. Our simulation results showcase the latency performance improvement and received signal-to-noise ratio with different variations of the proposed scheme over the optimum beam training scheme based on exhaustive narrow beam search.Comment: 7 pages; 6 figures; accepted to an IEEE conferenc