arXiv subjects

Olivier Michel

Publications and source records attributed to Olivier Michel.

13 recordsLinked to original sources

arXiv2025

ICT Within Limits Is Bound To Be Old-Fashioned By Design

Crossing multiple planetary boundaries places us in a zone of uncertainty that is characterized by considerable fluctuations in climatic events. The situation is exacerbated by the relentless use of resources and energy required to develop digital infrastructures that have become pervasive and ubiquitous. We are bound to these infrastructures, dead technologies and negative commons, just as much as they bind us. Although their growth threatens the necessary reduction of our impact, we have a responsibility to maintain them until we can do without them. In university setting, as well as in any public organization, urban mines per se, we propose an IT architecture based on the exclusive use of unreliable waste from electrical and electronic equipment (WEEE) as a frugal alternative to the incessant replacement of devices. Powered by renewable energy, autonomous, robust, adaptable, and built on battle-tested open-source software, we envision this solution for a situation where use is bound to decline eventually, to close this damaging technological chapter. Digital technology, the idol of modern times, is to meet its twilight if we do not want to irrevocably alter the critical zone.

cs.CY↗

arXiv2022

Multivariate Normality test for colored data

Performances of the Multivariate Kurtosis are investigated when applied to colored data, with or without Auto-Regressive pre-whitening, and with or without projection onto a lower-dimensional random subspace. Computer experiments demonstrate the importance of taking into account the possible color of the process in calculating the power of the normality test, in all the scenarios.

stat.ME↗

arXiv2022

A Normality Test for Multivariate Dependent Samples

Most normality tests in the literature are performed for scalar and independent samples. Thus, they become unreliable when applied to colored processes, hampering their use in realistic scenarios.We focus on Mardia's multivariate kurtosis, derive closed-form expressions of its asymptotic distribution for statistically dependent samples, under the null hypothesis of normality and a mixing condition. The calculus is long and tedious but the final result is simple and is implemented with a low computational burden. The proposed expression of the test power exhibits good properties on various scenarios; this is illustrated by computer experiments by means of copulas.

stat.ME↗

arXiv2022

Joint Normality Test Via Two-Dimensional Projection

Extensive literature exists on how to test for normality, especially for identically and independently distributed (i.i.d) processes. The case of dependent samples has also been addressed, but only for scalar random processes. For this reason, we have proposed a joint normality test for multivariate time-series, extending Mardia's Kurtosis test. In the continuity of this work, we provide here an original performance study of the latter test applied to two-dimensional projections. By leveraging copula, we conduct a comparative study between the bivariate tests and their scalar counterparts. This simulation study reveals that one-dimensional random projections lead to notably less powerful tests than two-dimensional ones.

eess.SP↗

arXiv2019

Optimal Measurement Times for a Small Number of Measures of a Brownian Motion over a Finite Period

The measure timetable plays a critical role for the accuracy of the estimator. This article deals with the optimization of the schedule of measures for observing a random process in time using a Kalman filter, when the length of the process is finite and fixed, and a fixed number of measures are available. The measuring devices are allowed to differ. The mean variance of the estimator is chosen as criterion for optimality. The cases of $1$ or $2$ measures are studied in detail, and analytical formulas are provided.

eess.SP↗

arXiv2017

Robust control of varying weak hyperspectral target detection with sparse non-negative representation

In this study, a multiple-comparison approach is developed for detecting faint hyperspectral sources. The detection method relies on a sparse and non-negative representation on a highly coherent dictionary to track a spatially varying source. A robust control of the detection errors is ensured by learning the test statistic distributions on the data. The resulting control is based on the false discovery rate, to take into account the large number of pixels to be tested. This method is applied to data recently recorded by the three-dimensional spectrograph Multi-Unit Spectrograph Explorer.

stat.ME↗

arXiv2016

Multidimensional factorization through helical mapping

This paper proposes a new perspective on the problem of multidimensional spectral factorization, through helical mapping: $d$-dimensional ($d$D) data arrays are vectorized, processed by $1$D cepstral analysis and then remapped onto the original space. Partial differential equations (PDEs) are the basic framework to describe the evolution of physical phenomena. We observe that the minimum phase helical solution asymptotically converges to the $d$D semi-causal solution, and allows to decouple the two solutions arising from PDEs describing physical systems. We prove this equivalence in the theoretical framework of cepstral analysis, and we also illustrate the validity of helical factorization through a $2$D wave propagation example and a $3$D application to helioseismology.

cs.IT↗

arXiv2015

Inter-sensor propagation delay estimation using sources of opportunity

Propagation delays are intensively used for Structural Health Monitoring or Sensor Network Localization. In this paper, we study the performances of acoustic propagation delay estimation between two sensors, using sources of opportunity only. Such sources are defined as being uncontrolled by the user (activation time, location, spectral content in time and space), thus preventing the direct estimation with classical active approaches, such as TDOA, RSSI and AOA. Observation models are extended from the literature to account for the spectral characteristics of the sources in this passive context and we show how time-filtered sources of opportunity impact the retrieval of the propagation delay between two sensors. A geometrical analogy is then proposed that leads to a lower bound on the variance of the propagation delay estimation that accounts for both the temporal and the spatial properties of the sources field.

physics.class-ph↗

arXiv2011

Algorithm for Sensor Network Attitude Problem

Sensor network attitude problem consists in retrieving the attitude of each sensor of a network knowing some relative orientations between pairs of sensors. The attitude of a sensor is its orientation in an absolute axis system. We present in this paper a method for solving the sensor network attitude problem using quaternion formalism which allows to apply linear algebra tools. The proposed algorithm solves the problem when all of the relative attitudes are known. A complete characterisation of the algorithm is established: spatial complexity, time complexity and robustness. Our algorithm is validated in simulations and with real experiments.

math.OC↗

arXiv2011

Passive tomography for elastic waves in solids

In this paper we derive relations between the cross-correlation of ambient noises recorded at two different points and the Green's function of the elastic waves in a medium with viscous damping. The Green's function allows to estimate physical parameters such as speeds or distances. Furthermore, this work is extended by introducing the Green's correlation function proposed by J-L. Lacoume in [Lacoume07]. Some recent works proved the possible reconstruction of the Green's function for scalar waves from the cross-correlation function of ambient noise. In this work, we consider vector waves propagating in a three dimensional solid medium. Two approaches are developed. Firstly, we extend theoretical derivations proposed by Y. Colin de Verdi`ere in [ColinDeVerdiere09], relating cross-correlation of scalar waves to 1D Green's function using linear operator theory. The second approach recasts the three dimensional problem in the framework of Fourier theory. This allows to improve physical understanding of the underlying physical processes as outlined in [Lacoume07].

cond-mat.other↗

arXiv2010

Variable elimination for building interpreters

In this paper, we build an interpreter by reusing host language functions instead of recoding mechanisms of function application that are already available in the host language (the language which is used to build the interpreter). In order to transform user-defined functions into host language functions we use combinatory logic : lambda-abstractions are transformed into a composition of combinators. We provide a mechanically checked proof that this step is correct for the call-by-value strategy with imperative features.

cs.SE↗

arXiv2004

WebotsTM: Professional Mobile Robot Simulation

Cyberbotics Ltd. develops WebotsTM, a mobile robotics simulation software that provides you with a rapid prototyping environment for modelling, programming and simulating mobile robots. The provided robot libraries enable you to transfer your control programs to several commercially available real mobile robots. WebotsTM lets you define and modify a complete mobile robotics setup, even several different robots sharing the same environment. For each object, you can define a number of properties, such as shape, color, texture, mass, friction, etc. You can equip each robot with a large number of available sensors and actuators. You can program these robots using your favorite development environment, simulate them and optionally transfer the resulting programs onto your real robots. WebotsTM has been developed in collaboration with the Swiss Federal Institute of Technology in Lausanne, thoroughly tested, well documented and continuously maintained for over 7 years. It is now the main commercial product available from Cyberbotics Ltd.

cs.RO↗

arXiv1998

Detection of Coherent Vorticity Structures using Time-Scale Resolved Acoustic Spectroscopy

We describe here an experimental technique based on the acoustic scattering phenomenon allowing the direct probing of the vorticity field in a turbulent flow. Using time-frequency distributions, recently introduced in signal analysis theory, for the analysis of the scattered acoustic signals, we show how the legibility of these signals is significantly improved (time resolved spectroscopy). The method is illustrated on data extracted from a highly turbulent jet flow : discrete vorticity events are clearly evidenced. We claim that the recourse to time-frequency distributions lead to an operational definition of coherent structures associated with phase stationarity in the time-frequency plane.

chao-dyn↗