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Cédric Join

Bio: Cédric Join is an academic researcher from University of Lorraine. The author has contributed to research in topics: Nonlinear system & Fault detection and isolation. The author has an hindex of 32, co-authored 178 publications receiving 4562 citations. Previous affiliations of Cédric Join include Nancy-Université & Concordia University Wisconsin.


Papers
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TL;DR: In this article, two new technical indicators for trading systems and risk management are derived from trends in time series, the existence of which has been recently mathematically demonstrated by the same authors.
Abstract: We derive two new technical indicators for trading systems and risk management. They stem from trends in time series, the existence of which has been recently mathematically demonstrated by the same authors (A mathematical proof of the existence of trends in financial time series, Proc. Int. Conf. Systems Theory: Modelling, Analysis and Control, Fes, 2009), and from higher order quantities which replace the familiar statistical tools. Recent fast estimation techniques of algebraic flavor are utilized. The first indicator tells us if the future price will be above or below the forecasted trendline. The second one predicts abrupt changes. Several promising numerical experiments are detailed and commented.

12 citations

27 May 2011
TL;DR: The regulation of freeway traffic flow is achieved via the newly introduced model-free control, which is easy to implement and shows good robustness properties with respect to perturbations.
Abstract: The regulation of freeway traffic flow, which is a complex nonlinear system, is achieved via the newly introduced model-free control. Several computer simulations are validating our control strategy, which is easy to implement and shows good robustness properties with respect to perturbations

12 citations

Proceedings ArticleDOI
06 Jan 2020
TL;DR: This article proposes a control architecture with model-free control algorithms that is able to stabilize the hybrid MAV’s attitude, velocity, and position without any modeling process and validate the MFC architecture according to a comprehensive set of flight simulations and real flight experiments.
Abstract: Hybrid Micro Air Vehicles (MAVs) combine the beneficial features of rotorcraft with fixed-wing configurations providing a complete flight envelope that includes vertical take-off, hover, transitioning flights, forward flight and vertical landing. Tailsitter MAVs belong to a particular class of hybrid MAVs and its peculiar issue is related to the transitioning flight phase where, for high incidence angles, fast changing of aerodynamic forces and moments are observed which are difficult to model and control accurately. To overcome this issue, we proposed a control architecture with model-free control (MFC) algorithms that has been able to stabilize the hybrid MAV's attitude, velocity, and position without any modeling process. The proposed control architecture consisted basically two steps~: 1) The attitude control, to ensure the hybrid MAV's attitude tracking and stability within the entire flight envelope; 2) The guidance system responsible to control both velocity and position. We validated the MFC architecture according to a comprehensive set of flight simulations and experimental flight tests. Experimental flight tests shown an effective and promising control strategy solving the principal issue of hybrid MAVs that was the formulation of accurate hybrid MAV's dynamic equations to design control laws. The obtained results have provided a straightforward way to validate the methodological principles presented in this article as well as to certify the designed MFC parameters, and to establish a conclusion regarding MFC benefits in both theoretical and practical contexts.

12 citations

Book ChapterDOI
20 Oct 2008
TL;DR: This paper proposes an original adaptation of an approach used into nonlinear control for fault-diagnosis and fault-tolerant control based on algebraic derivation and which is robust to noise.
Abstract: Extrema of curvature are useful key points for different image analysis tasks. Indeed, polygonal approximation or arc decomposition methods used often these points to initialize or to improve their algorithms. Several shape-based image retrieval methods focus also their descriptors on key points. This paper is focused on the detection of extrema of curvature points for a raster-to-vector-conversion framework. We propose an original adaptation of an approach used into nonlinear control for fault-diagnosis and fault-tolerant control based on algebraic derivation and which is robust to noise. The experimental results are promising and show the robustness of the approach when the contours are bathed into a high level speckled noise.

12 citations

Posted Content
TL;DR: In this paper, the existence of trends in financial time series, based on a theorem published in 1995 by P. Cartier and Y. Perrin, lead to a new understanding of option pricing and dynamic hedging.
Abstract: An elementary arbitrage principle and the existence of trends in financial time series, which is based on a theorem published in 1995 by P. Cartier and Y. Perrin, lead to a new understanding of option pricing and dynamic hedging. Intricate problems related to violent behaviors of the underlying, like the existence of jumps, become then quite straightforward by incorporating them into the trends. Several convincing computer experiments are reported.

11 citations


Cited by
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Journal ArticleDOI
TL;DR: A bibliographical review on reconfigurable fault-tolerant control systems (FTCS) is presented, with emphasis on the reconfiguring/restructurable controller design techniques.

2,455 citations

Book ChapterDOI
15 Feb 2011

1,876 citations

01 Nov 1981
TL;DR: In this paper, the authors studied the effect of local derivatives on the detection of intensity edges in images, where the local difference of intensities is computed for each pixel in the image.
Abstract: Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

1,829 citations