The Experts below are selected from a list of 2517 Experts worldwide ranked by ideXlab platform
Alain Oustaloup - One of the best experts on this subject based on the ideXlab platform.
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An overview of the CRONE approach in system analysis, modeling and identification, observation and control
IFAC Proceedings Volumes, 2016Co-Authors: Alain Oustaloup, Rachid Malti, Pierre Melchior, Xavier Moreau, Jocelyn Sabatier, Patrick Lanusse, Mathieu MozeAbstract:Abstract The aim of the paper is to present the fundamental definitions connected to Fractional Differentiation and to present an overview of the CRONE approach in the fields of system analysis, modeling and identification, observation and control. Industrial applications of Fractional Differentiation are also described in this paper. Some recent developments are also presented.
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instrumental variable method with optimal Fractional Differentiation order for continuous time system identification
IFAC Proceedings Volumes, 2009Co-Authors: Stéphane Victor, Rachid Malti, Alain OustaloupAbstract:this paper deals with continuous-time system identification using Fractional Differentiation models in a noisy output context. The simplified refined instrumental variable for continuous-time Fractional systems (srivcf) is extended to optimize the commensurate order with a gradient-based method as the coosrivcf algorithm. Simulation analysis is used to demonstrate the performance of the proposed optimal instrumental variable scheme combined with order optimization.
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Path tracking design based on Fractional prefilter with acceleration input and comparison with preshaper approach.
Transactions on Systems Signals and Devices Issue on "Systems Analysis & Automatic Control" Shaker-Verlag Publisher, 2008Co-Authors: Pierre Melchior, R. Jallouli-khlif, B. Orsoni, Nabil Derbel, Alain OustaloupAbstract:In path tracking design, the dynamic of actuators must be taken into account in order to reduce overshoots on the actuator outputs. Different methods were developed. One based on Fractional Differentiation allows the generation of optimal movement reference-input leading to a minimum path completion time, taking into account maximum velocity and acceleration and the bandwidth of the system. Different strategies were developed. In this paper, Fractional Differentiation is used through a Davidson-Cole prefilter with acceleration bang bang input to ensure continuity on acceleration and jerk signals. In order to compare, a second approach, based on preshaper synthesis, is presented; the shaped input is obtained by convolving desired input with an impulse sequence. The synthesis methodologies and performances of both methods are studied and compared on an example.
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an optimal instrumental variable method for continuous time Fractional model identification
IFAC Proceedings Volumes, 2008Co-Authors: Rachid Malti, Stéphane Victor, Alain Oustaloup, Hugues GarnierAbstract:Abstract this paper deals with continuous-time system identification using Fractional Differentiation models in a noisy output context. The simplified refined instrumental variable for continuous-time systems ( srivc ) is extended to Fractional models. Monte Carlo simulation analysis are used to demonstrate the performance of the proposed optimal instrumental variable scheme.
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Limited-Bandwidth Fractional Differentiator: Synthesis and Application in Vibration Isolation
Advances in Fractional Calculus, 2007Co-Authors: Pascal Serrier, Xavier Moreau, Alain OustaloupAbstract:The use of Fractional Differentiation in vehicle suspension design has many interests. This paper presents a hydropneumatic suspensions design method based on Fractional Differentiation. Once an hydraulic structure has been chosen for the suspension, it is possible to calculate the values of all technological parameters, so that the suspension force - deflection transfer function is a band-limited Fractional differentiator. The combination of the CRONE control methodology and of hydropneumatic technology leads to remarkable performances of robustness.
Patrick Siarry - One of the best experts on this subject based on the ideXlab platform.
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Mobile indoor location based on Fractional Differentiation
2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012Co-Authors: Mustapha Dakkak, Amir Nakib, Patrick Siarry, Boubaker Daachi, Jacques LemoineAbstract:While the static indoor location of a mobile terminal (MT) has been extensively studied on last decade, the prediction of the trajectory of a MT still is the major problem for building mobile location (tracking) systems (TSs). This problem is solved for outdoor TSs using global positioning system (GPS), however, it remains an essential obstacle to construct reliable indoor TSs. Different approaches were proposed in the literature, the most used is that based on prediction filters, such as linear filters (LF), Kalman filters (KF) and particle filters (PF). In this paper, we propose to enhance the performance of the predictors using digital Fractional Differentiation (DFD) to predict a MT trajectory. To illustrate the obtained results, three indoor trajectory scenarios inspired from real daily promenades are simulated (museum visit, hospital doctor walking and shopping in the market). Experimental results show a significant improvement of the performance of the classical predictors, particularly in noisy cases.
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WCNC - Mobile indoor location based on Fractional Differentiation
2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012Co-Authors: Mustapha Dakkak, Amir Nakib, Patrick Siarry, Boubaker Daachi, Jacques LemoineAbstract:While the static indoor location of a mobile terminal (MT) has been extensively studied on last decade, the prediction of the trajectory of a MT still is the major problem for building mobile location (tracking) systems (TSs). This problem is solved for outdoor TSs using global positioning system (GPS), however, it remains an essential obstacle to construct reliable indoor TSs. Different approaches were proposed in the literature, the most used is that based on prediction filters, such as linear filters (LF), Kalman filters (KF) and particle filters (PF). In this paper, we propose to enhance the performance of the predictors using digital Fractional Differentiation (DFD) to predict a MT trajectory. To illustrate the obtained results, three indoor trajectory scenarios inspired from real daily promenades are simulated (museum visit, hospital doctor walking and shopping in the market). Experimental results show a significant improvement of the performance of the classical predictors, particularly in noisy cases.
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third brain ventricle deformation analysis using Fractional Differentiation and evolution strategy in brain cine mri
Proceedings of SPIE, 2010Co-Authors: Amir Nakib, Patrick Siarry, Fazia Aiboud, Jerome Hodel, Philippe DecqAbstract:In this paper, we present an original method to evaluate the deformations in the third cerebral ventricle on a brain cine- MR imaging. First, a segmentation process, based on a Fractional Differentiation method, is directly applied on a 2D+t dataset to detect the contours of the region of interest (i.e. lamina terminalis ). Then, the successive segmented contours are matched using a procedure of global alignment, followed by a morphing process, based on the Covariance Matrix Adaptation Evolution Strategy (CMAES). Finally, local measurements of deformations are derived from the previously determined matched contours. The validation step is realized by comparing our results with the measurements achieved on the same patients by an expert.
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Medical Imaging: Image Processing - Third brain ventricle deformation analysis using Fractional Differentiation and evolution strategy in brain cine-MRI
Proceedings of SPIE, 2010Co-Authors: Amir Nakib, Patrick Siarry, Fazia Aiboud, Jerome Hodel, Philippe DecqAbstract:In this paper, we present an original method to evaluate the deformations in the third cerebral ventricle on a brain cine- MR imaging. First, a segmentation process, based on a Fractional Differentiation method, is directly applied on a 2D+t dataset to detect the contours of the region of interest (i.e. lamina terminalis ). Then, the successive segmented contours are matched using a procedure of global alignment, followed by a morphing process, based on the Covariance Matrix Adaptation Evolution Strategy (CMAES). Finally, local measurements of deformations are derived from the previously determined matched contours. The validation step is realized by comparing our results with the measurements achieved on the same patients by an expert.
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a thresholding method based on two dimensional Fractional Differentiation
Image and Vision Computing, 2009Co-Authors: Amir Nakib, Hamouche Oulhadj, Patrick SiarryAbstract:In this paper, we present a new thresholding technique based on two-dimensional Fractional Differentiation, that was obtained through the extension of the one-dimensional Fractional Differentiation. A new geometric interpretation of the two-dimensional Fractional Differentiation is also presented in the paper. The proposed method exploits the properties and the interpretations of the two-dimensional Fractional Differentiation. It is based on the assumption that there is a dependency between the pixels' gray-levels, that is translated into a correlation between pixels describing the same object. The effectiveness of the proposed method is demonstrated by using examples from real-world and synthetic images.
Amir Nakib - One of the best experts on this subject based on the ideXlab platform.
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Mobile indoor location based on Fractional Differentiation
2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012Co-Authors: Mustapha Dakkak, Amir Nakib, Patrick Siarry, Boubaker Daachi, Jacques LemoineAbstract:While the static indoor location of a mobile terminal (MT) has been extensively studied on last decade, the prediction of the trajectory of a MT still is the major problem for building mobile location (tracking) systems (TSs). This problem is solved for outdoor TSs using global positioning system (GPS), however, it remains an essential obstacle to construct reliable indoor TSs. Different approaches were proposed in the literature, the most used is that based on prediction filters, such as linear filters (LF), Kalman filters (KF) and particle filters (PF). In this paper, we propose to enhance the performance of the predictors using digital Fractional Differentiation (DFD) to predict a MT trajectory. To illustrate the obtained results, three indoor trajectory scenarios inspired from real daily promenades are simulated (museum visit, hospital doctor walking and shopping in the market). Experimental results show a significant improvement of the performance of the classical predictors, particularly in noisy cases.
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WCNC - Mobile indoor location based on Fractional Differentiation
2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012Co-Authors: Mustapha Dakkak, Amir Nakib, Patrick Siarry, Boubaker Daachi, Jacques LemoineAbstract:While the static indoor location of a mobile terminal (MT) has been extensively studied on last decade, the prediction of the trajectory of a MT still is the major problem for building mobile location (tracking) systems (TSs). This problem is solved for outdoor TSs using global positioning system (GPS), however, it remains an essential obstacle to construct reliable indoor TSs. Different approaches were proposed in the literature, the most used is that based on prediction filters, such as linear filters (LF), Kalman filters (KF) and particle filters (PF). In this paper, we propose to enhance the performance of the predictors using digital Fractional Differentiation (DFD) to predict a MT trajectory. To illustrate the obtained results, three indoor trajectory scenarios inspired from real daily promenades are simulated (museum visit, hospital doctor walking and shopping in the market). Experimental results show a significant improvement of the performance of the classical predictors, particularly in noisy cases.
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third brain ventricle deformation analysis using Fractional Differentiation and evolution strategy in brain cine mri
Proceedings of SPIE, 2010Co-Authors: Amir Nakib, Patrick Siarry, Fazia Aiboud, Jerome Hodel, Philippe DecqAbstract:In this paper, we present an original method to evaluate the deformations in the third cerebral ventricle on a brain cine- MR imaging. First, a segmentation process, based on a Fractional Differentiation method, is directly applied on a 2D+t dataset to detect the contours of the region of interest (i.e. lamina terminalis ). Then, the successive segmented contours are matched using a procedure of global alignment, followed by a morphing process, based on the Covariance Matrix Adaptation Evolution Strategy (CMAES). Finally, local measurements of deformations are derived from the previously determined matched contours. The validation step is realized by comparing our results with the measurements achieved on the same patients by an expert.
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Medical Imaging: Image Processing - Third brain ventricle deformation analysis using Fractional Differentiation and evolution strategy in brain cine-MRI
Proceedings of SPIE, 2010Co-Authors: Amir Nakib, Patrick Siarry, Fazia Aiboud, Jerome Hodel, Philippe DecqAbstract:In this paper, we present an original method to evaluate the deformations in the third cerebral ventricle on a brain cine- MR imaging. First, a segmentation process, based on a Fractional Differentiation method, is directly applied on a 2D+t dataset to detect the contours of the region of interest (i.e. lamina terminalis ). Then, the successive segmented contours are matched using a procedure of global alignment, followed by a morphing process, based on the Covariance Matrix Adaptation Evolution Strategy (CMAES). Finally, local measurements of deformations are derived from the previously determined matched contours. The validation step is realized by comparing our results with the measurements achieved on the same patients by an expert.
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a thresholding method based on two dimensional Fractional Differentiation
Image and Vision Computing, 2009Co-Authors: Amir Nakib, Hamouche Oulhadj, Patrick SiarryAbstract:In this paper, we present a new thresholding technique based on two-dimensional Fractional Differentiation, that was obtained through the extension of the one-dimensional Fractional Differentiation. A new geometric interpretation of the two-dimensional Fractional Differentiation is also presented in the paper. The proposed method exploits the properties and the interpretations of the two-dimensional Fractional Differentiation. It is based on the assumption that there is a dependency between the pixels' gray-levels, that is translated into a correlation between pixels describing the same object. The effectiveness of the proposed method is demonstrated by using examples from real-world and synthetic images.
Bo Fang - One of the best experts on this subject based on the ideXlab platform.
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asymptotic analysis of an axially viscoelastic string constituted by a Fractional Differentiation law
International Journal of Non-linear Mechanics, 2013Co-Authors: Tianzhi Yang, Bo FangAbstract:Abstract The non-linear creep vibration of an axially moving string constituted by a Fractional Differentiation law is investigated in this paper. A non-linear partial Fractional order differential equation governing the transverse vibration of the string is derived from Newton's second law, the Fractional derivative Kelvin constitutive relationship and the Lagrangian strain. Unlike the classic models, the derived governing equation takes creep behavior into account. By using the multi-scale method, the non-linear frequency of the axially moving string is obtained. The results show that the amplitude predicted by the Fractional model is larger than that predicted by the viscoelastic solid models.
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dynamics of vibration isolation system obeying Fractional Differentiation
Aircraft Engineering and Aerospace Technology, 2012Co-Authors: Song Li, Tianzhi Yang, Bo Fang, Yewei Zhang, Wenhu HuangAbstract:Purpose – The purpose of this paper is to analyze a new, whole‐spacecraft isolator and its performance of vibration isolation, which has been designed to ensure spacecraft safety at the launching stage.Design/methodology/approach – The design is based on the analysis of Fractional derivative stress‐strain constitutive relationship of viscoelastic materials. First, the authors study the constitutive relationships for viscoelastic solid of the damping materials, then the authors introduce the results obtained to the equations of motion for the damped isolator.Findings – By performing a series of transformation, the authors obtain the analytical solution of the equations. It is shown that the results compare favourably to the numerical simulations and experiments. In addition, a saturation phenomenon for the first order damping ratio is also discussed.Practical implications – It is found that the constitutive relationships written in terms of the Fractional calculus can be applied in the system function of t...
Adrienne L Fairhall - One of the best experts on this subject based on the ideXlab platform.
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capturing multiple timescales of adaptation to second order statistics with generalized linear models gain scaling and Fractional Differentiation
Frontiers in Systems Neuroscience, 2020Co-Authors: Kenneth W Latimer, Adrienne L FairhallAbstract:Single neurons can dynamically change the gain of their spiking responses to take into account shifts in stimulus variance. Moreover, gain adaptation can occur across multiple timescales. Here, we examine the ability of a simple statistical model of spike trains, the generalized linear model (GLM), to account for these adaptive effects. The GLM describes spiking as a Poisson process whose rate depends on a linear combination of the stimulus and recent spike history. The GLM successfully replicates gain scaling observed in Hodgkin-Huxley simulations of cortical neurons that occurs when the ratio of spike-generating potassium and sodium conductances approaches one. Gain scaling in the GLM depends on the length and shape of the spike history filter. Additionally, the GLM captures adaptation that occurs over multiple timescales as a Fractional derivative of the stimulus envelope, which has been observed in neurons that include long timescale afterhyperpolarization conductances. Fractional Differentiation in GLMs requires long spike history that span several seconds. Together, these results demonstrate that the GLM provides a tractable statistical approach for examining single-neuron adaptive computations in response to changes in stimulus variance.
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capturing multiple timescales of adaptation to second order statistics with generalized linear models gain scaling and Fractional Differentiation
bioRxiv, 2019Co-Authors: Kenneth W Latimer, Adrienne L FairhallAbstract:Single neurons can dynamically change the gain of their spiking responses to account for shifts in stimulus variance. Moreover, gain adaptation can occur across multiple timescales. Here, we examine the ability of a simple statistical model of spike trains, the generalized linear model (GLM), to account for these adaptive effects. The GLM describes spiking as a Poisson process whose rate depends on a linear combination of the stimulus and recent spike history. The GLM successfully replicates gain scaling observed in Hodgkin-Huxley simulations of cortical neurons that occurs when the ratio of spike-generating potassium and sodium conductances approaches one. Gain scaling in the GLM depends on the length and shape of the spike history filter. Additionally, the GLM captures adaptation that occurs over multiple timescales as a Fractional derivative of the stimulus variance, which has been observed in neurons that include long timescale afterhyperpolarization conductances. Fractional Differentiation in GLMs requires long spike history that span several seconds. Together, these results demonstrate that the GLM provides a tractable statistical approach for examining single-neuron adaptive computations in response to changes in stimulus variance.
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Fractional Differentiation by neocortical pyramidal neurons
Nature Neuroscience, 2008Co-Authors: Brian Nils Lundstrom, Matthew H Higgs, William J Spain, Adrienne L FairhallAbstract:Neural systems adapt to changes in stimulus statistics. The authors find that neocortical pyramidal neurons adapt with a time scale that depends on the time scale of changes in stimulus statistics, and that for individual neurons the firing is a Fractional derivative of slowly varying stimulus parameters. Neural systems adapt to changes in stimulus statistics. However, it is not known how stimuli with complex temporal dynamics drive the dynamics of adaptation and the resulting firing rate. For single neurons, it has often been assumed that adaptation has a single time scale. We found that single rat neocortical pyramidal neurons adapt with a time scale that depends on the time scale of changes in stimulus statistics. This multiple time scale adaptation is consistent with Fractional order Differentiation, such that the neuron's firing rate is a Fractional derivative of slowly varying stimulus parameters. Biophysically, even though neuronal Fractional Differentiation effectively yields adaptation with many time scales, we found that its implementation required only a few properly balanced known adaptive mechanisms. Fractional Differentiation provides single neurons with a fundamental and general computation that can contribute to efficient information processing, stimulus anticipation and frequency-independent phase shifts of oscillatory neuronal firing.
