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Bigand A.,LISIC ULCO | Colot O.,CNRS Lille Research Center in Informatics, Signal and Automatic control
Fuzzy Sets and Systems | Year: 2015

Models based on interval-valued fuzzy sets make it possible to manage numerical and spatial uncertainty in grey-scale values of image pixels. In a recent paper, we proposed a method that links the ultrafuzziness index (that makes it possible to take into account some uncertainty, like noise, and inherent to image capture) with impulse noise removal. However, computing with interval-valued fuzzy sets requires assigning their membership functions (MFs). The present article proposes a novel method for the generation of membership functions, based on image histogram, to remedy that drawback and it complements our previous study. The performance of the method is evaluated by applying this technique to the particular case of Gaussian noise detection and reduction, which remains a crucial issue for image processing. Experimental results have demonstrated that the proposed method leads to interval-valued fuzzy filters that are comparable with some well-known conventional and fuzzy filters, especially in the case of iterative filtering methods. Image details are preserved while reducing Gaussian noise, and the link between image noise and interval-valued fuzzy sets is thus verified. The main advantage of the proposed technique is to use basic image information, namely an image histogram, which is easy to obtain. © 2015 Elsevier B.V.

Jha M.S.,Ecole Centrale Lille | Dauphin-Tanguy G.,Ecole Centrale Lille | Ould-Bouamama B.,CNRS Lille Research Center in Informatics, Signal and Automatic control
Mechanical Systems and Signal Processing | Year: 2016

The paper's main objective is to address the problem of health monitoring of system parameters in Bond Graph (BG) modeling framework, by exploiting its structural and causal properties. The system in feedback control loop is considered uncertain globally. Parametric uncertainty is modeled in interval form. The system parameter is undergoing degradation (prognostic candidate) and its degradation model is assumed to be known a priori. The detection of degradation commencement is done in a passive manner which involves interval valued robust adaptive thresholds over the nominal part of the uncertain BG-derived interval valued analytical redundancy relations (I-ARRs). The latter forms an efficient diagnostic module. The prognostics problem is cast as joint state-parameter estimation problem, a hybrid prognostic approach, wherein the fault model is constructed by considering the statistical degradation model of the system parameter (prognostic candidate). The observation equation is constructed from nominal part of the I-ARR. Using particle filter (PF) algorithms; the estimation of state of health (state of prognostic candidate) and associated hidden time-varying degradation progression parameters is achieved in probabilistic terms. A simplified variance adaptation scheme is proposed. Associated uncertainties which arise out of noisy measurements, parametric degradation process, environmental conditions etc. are effectively managed by PF. This allows the production of effective predictions of the remaining useful life of the prognostic candidate with suitable confidence bounds. The effectiveness of the novel methodology is demonstrated through simulations and experiments on a mechatronic system. © 2016 Elsevier Ltd.

Chainais P.,CNRS Lille Research Center in Informatics, Signal and Automatic control | Leray A.,Laboratory Interdisciplinaire Carnot de Bourgogne
IEEE Transactions on Image Processing | Year: 2016

The registration process is a key step for super-resolution (SR) reconstruction. More and more devices permit to overcome this bottleneck using a controlled positioning system, e.g., sensor shifting using a piezoelectric stage. This makes possible to acquire multiple images of the same scene at different controlled positions. Then, a fast SR algorithm can be used for efficient SR reconstruction. In this case, the optimal use of r{2} images for a resolution enhancement factor r is generally not enough to obtain satisfying results due to the random inaccuracy of the positioning system. Thus, we propose to take several images around each reference position. We study the error produced by the SR algorithm due to spatial uncertainty as a function of the number of images per position. We obtain a lower bound on the number of images that is necessary to ensure a given error upper bound with probability higher than some desired confidence level. Such results give precious hints to the design of SR systems. © 1992-2012 IEEE.

Sun Y.,SantAnna School of Advanced Studies | Lipari G.,CNRS Lille Research Center in Informatics, Signal and Automatic control
Real-Time Systems | Year: 2015

In this paper we present an exact schedulability test for sporadic real-time tasks scheduled by the Global Fixed Priority Fully Preemptive Scheduler on a multiprocessor system. The analysis consists in modeling the system as a Linear Hybrid Automaton, and in performing a reachability analysis for states representing deadline miss conditions. To mitigate the problem of state space explosion, we propose a pre-order relationship over the symbolic states of the model: states that are simulated by others can be safely eliminated from the state space. We also formulate the concept of decidability interval with respect to a set of constrained-deadline sporadic tasks on multiprocessor. The decidability interval is a bounded time interval such that, if a deadline miss occurs in the schedule, then it is possible to find a configuration of arrival times for the tasks such that the deadline miss happens within the bounded interval. Vice versa, if no configuration of arrival times produces a deadline miss in the bounded interval, then no deadline miss is ever possible in the schedule. Hence we prove that the schedulability analysis problem is decidable, and we provide a formula for computing the decidability interval. To our knowledge, this is the first time such a time interval is proposed for sporadic tasks running on multiprocessor. The proposed schedulability analysis has been implemented in a software tool. For the first time we assess the pessimism of the state-of-the-art approximate schedulability test through experiments. Moreover, we show that the use of the proposed model permits to analyse tasks with more general parameter values than other exact algorithms in the literature. Nevertheless, even with our approach the complexity remains too high for analysing practical task sets with more than seven tasks. © 2015 Springer Science+Business Media New York

Sun Y.,SantAnna School of Advanced Studies | Lipari G.,CNRS Lille Research Center in Informatics, Signal and Automatic control
Proceedings - Real-Time Systems Symposium | Year: 2016

We address the problem of schedulability analysis for a set of sporadic real-time tasks scheduled by the Global Earliest Deadline First (G-EDF) policy on a multiprocessor platform. State-of-the-art tests for schedulability analysis of multiprocessor global scheduling are often incomparable. That is, a task set that is judged not schedulable by a test may be verified to be schedulable by another test, and vice versa. In this paper, we first develop a new schedulability test that integrates the limited carry-in technique and Response Time Analysis (RTA) procedure for Global EDF schedulability analysis. Then, we provide an over-approximate variant of this test with better run-time efficiency. Later, we extend these two tests to self-suspending tasks. All schedulability tests proposed in the paper have provable dominance over their state-of-the-art counterparts. Finally, we conduct extensive comparisons among different schedulability tests. Our new tests show significant improvements for schedulability analysis of Global EDF. © 2015 IEEE.

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