Priori Knowledge

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Christine Henry - One of the best experts on this subject based on the ideXlab platform.

  • model based optimal multipolar stimulation without a Priori Knowledge of nerve structure application to vagus nerve stimulation
    Journal of Neural Engineering, 2018
    Co-Authors: Melissa Dali, Olivier Rossel, David Andreu, Laure Laporte, Alfredo Hernandez, Jeremy Laforet, Eloi Marijon, Albert Hagege, Maureen Clerc, Christine Henry
    Abstract:

    Objective - Multipolar cuff electrode can selectively stimulate areas of peripheral nerves and therefore enable to control independent functions. However, the branching and fascicularization are known for a limited set of nerves and the specific organization remains subject-dependent. This paper presents general modeling and optimization methods in the context of multipolar stimulation using a cuff electrode without a Priori Knowledge of the nerve structure. Vagus nerve stimulation experiments based on the optimization results were then investigated. Approach - The model consisted of two independent components: a lead field matrix representing the transfer function from the applied current to the extracellular voltage present on the nodes of Ranvier along each axon, and a linear activation model. The optimization process consisted in finding the best current repartition (ratios) to reach activation of a targeted area depending on three criteria: selectivity, efficiency and robustness. Main results - The results showed that state-of-the-art configurations (tripolar transverse, tripolar longitudinal) were part of the optimized solutions but new ones could emerge depending on the trade-off between the three criteria and the targeted area. Besides, the choice of appropriate current ratios was more important than the choice of the stimulation amplitude for a stimulation without a Priori Knowledge of the nerve structure. We successfully assessed the solutions in vivo to selectively induce a decrease in cardiac rhythm through vagus nerve stimulation while limiting side effects. Compared to the standard whole ring configuration, a selective solution found by simulation provided on average 2.6 less adverse effects. Significance - The preliminary results showed the rightness of the simulation, using a generic nerve geometry. It suggested that this approach will have broader applications that would benefit from multicontact cuff electrodes to elicit selective responses. In the context of the vagus nerve stimulation for heart failure therapy, we show that the simulation results were confirmed and improved the therapy while decreasing the side effects.

Gerhard Krieger - One of the best experts on this subject based on the ideXlab platform.

  • a Priori Knowledge based post doppler stap for traffic monitoring applications
    International Geoscience and Remote Sensing Symposium, 2012
    Co-Authors: Stefan V. Baumgartner, Gerhard Krieger
    Abstract:

    In this paper an extension of our “Fast GMTI Algorithm for Traffic Monitoring Based on A Priori Knowledge” [1,2] to an arbitrary number of M receiving (RX) channels is presented. This is done by incorporating Post-Doppler space-time adaptive processing into the processing chain. In contrast to our original dual-channel algorithm this additionally allows for robust estimation of the direction-of-arrival (DOA) angles of the detected signals. As a consequence false detections can be recognized and discarded. In the paper the processing chain is explained and performance estimation results for DLR's multi-channel airborne F-SAR system are presented and discussed.

  • Fast GMTI algorithm for traffic monitoring based on a Priori Knowledge
    IEEE Transactions on Geoscience and Remote Sensing, 2012
    Co-Authors: Stefan V. Baumgartner, Gerhard Krieger
    Abstract:

    In this paper, a fast a Priori Knowledge-based ground moving target indication and parameter estimation algorithm applicable to single- as well as to multichannel synthetic aperture airborne radar data is presented. The algorithm operates directly on range-compressed data. Only the intersection points of the moving vehicle signals with the a Priori known road axes, which are mapped into the range-compressed data array, are evaluated. For moving vehicle detection and parameter estimation, basically only a single 1-D fast Fourier transformation has to be performed for each considered road point. Hence, the required computational power is low, and the algorithm is well suited for real-time traffic monitoring applications. The proposed algorithm enables the estimation of the position and velocity vectors of detected moving vehicles independent of the number of channels. A single-channel synthetic aperture radar system may be sufficient in case of fast moving vehicles. The paper includes a detailed performance assessment together with experimental results that demonstrate the applicability in a real-world scenario.

  • real time road traffic monitoring using a fast a Priori Knowledge based sar gmti algorithm
    International Geoscience and Remote Sensing Symposium, 2010
    Co-Authors: Stefan V. Baumgartner, Gerhard Krieger
    Abstract:

    Radar systems operating on high altitude platforms can provide traffic information over wide areas, independent of sunlight illumination and weather conditions. In the paper, a novel a Priori Knowledge based ground moving target indication (GMTI) and parameter estimation algorithm applicable on single- as well as on multi-channel synthetic aperture radar (SAR) data is presented. Only the intersection points of the moving vehicle signals with the a Priori known road axes, which are mapped into the range-compressed data domain, are evaluated. The algorithm needs low computational load and is hence well suited for real-time traffic monitoring applications.

  • a Priori Knowledge based gmti algorithm for traffic monitoring applications
    Synthetic Aperture Radar (EUSAR) 2010 8th European Conference on, 2010
    Co-Authors: Stefan V. Baumgartner, Gerhard Krieger
    Abstract:

    In the paper a ground moving target indication and parameter estimation algorithm applicable on single- as well as on multi-channel synthetic aperture radar data is presented. The algorithm is based on a Priori Knowledge and operates directly on range-compressed data. Only the intersection points of the moving vehicle signals with the a Priori known road axes, which are mapped into the range-compressed data domain, are evaluated. The algorithm needs low computational power and hence, it is suitable for real time traffic monitoring applications. The absolute velocities, the headings and the geocoded positions of the detected moving vehicles can be estimated. A verification of the algorithm is done using real dual-channel data acquired with DLR's new airborne system F-SAR.

Melissa Dali - One of the best experts on this subject based on the ideXlab platform.

  • model based optimal multipolar stimulation without a Priori Knowledge of nerve structure application to vagus nerve stimulation
    Journal of Neural Engineering, 2018
    Co-Authors: Melissa Dali, Olivier Rossel, David Andreu, Laure Laporte, Alfredo Hernandez, Jeremy Laforet, Eloi Marijon, Albert Hagege, Maureen Clerc, Christine Henry
    Abstract:

    Objective - Multipolar cuff electrode can selectively stimulate areas of peripheral nerves and therefore enable to control independent functions. However, the branching and fascicularization are known for a limited set of nerves and the specific organization remains subject-dependent. This paper presents general modeling and optimization methods in the context of multipolar stimulation using a cuff electrode without a Priori Knowledge of the nerve structure. Vagus nerve stimulation experiments based on the optimization results were then investigated. Approach - The model consisted of two independent components: a lead field matrix representing the transfer function from the applied current to the extracellular voltage present on the nodes of Ranvier along each axon, and a linear activation model. The optimization process consisted in finding the best current repartition (ratios) to reach activation of a targeted area depending on three criteria: selectivity, efficiency and robustness. Main results - The results showed that state-of-the-art configurations (tripolar transverse, tripolar longitudinal) were part of the optimized solutions but new ones could emerge depending on the trade-off between the three criteria and the targeted area. Besides, the choice of appropriate current ratios was more important than the choice of the stimulation amplitude for a stimulation without a Priori Knowledge of the nerve structure. We successfully assessed the solutions in vivo to selectively induce a decrease in cardiac rhythm through vagus nerve stimulation while limiting side effects. Compared to the standard whole ring configuration, a selective solution found by simulation provided on average 2.6 less adverse effects. Significance - The preliminary results showed the rightness of the simulation, using a generic nerve geometry. It suggested that this approach will have broader applications that would benefit from multicontact cuff electrodes to elicit selective responses. In the context of the vagus nerve stimulation for heart failure therapy, we show that the simulation results were confirmed and improved the therapy while decreasing the side effects.

Tomoaki Utsunomiya - One of the best experts on this subject based on the ideXlab platform.

  • an explicit application of partition of unity approach to xfem approximation for precise reproduction of a Priori Knowledge of solution
    International Journal for Numerical Methods in Engineering, 2014
    Co-Authors: Kazuki Shibanuma, Tomoaki Utsunomiya, Shuji Aihara
    Abstract:

    SUMMARY The application of the XFEM to fracture mechanics is effective, because a crack can be modeled independently from the meshes and a complex remeshing procedure can be avoided. However, the classical XFEM has an essential problem in the approximation of partially enriched elements, that is, blending elements, which causes a lack of accuracy. For the weighted XFEM, although the numerical results show the effective improvements, it was found that the issue of blending elements still remains upon detailed examination. In the present paper, the PU-XFEM is formulated as an explicit application of the partition of unity (PU) approach to the XFEM, in order to precisely reproduce a Priori Knowledge of the solution by enrichment. The PU-XFEM is applied to two-dimensional linear fracture mechanics, and its effectiveness is verified. It is consequently found out that the PU-XFEM precisely reproduces a Priori Knowledge of the solution and is therefore effective to completely solve the problem of the blending elements. Copyright © 2013 John Wiley & Sons, Ltd.

  • evaluation on reproduction of Priori Knowledge in xfem
    Finite Elements in Analysis and Design, 2011
    Co-Authors: Kazuki Shibanuma, Tomoaki Utsunomiya
    Abstract:

    The XFEM is a numerical method which employs an approximation including the Priori Knowledge of the solution by using the concept of enrichment in a local area. In this paper, the reproductions of the Priori Knowledge in the original XFEM and the PUFEM-based XFEM for the crack analysis were evaluated, respectively. The results showed that there is a serious lack of the reproduction of the Priori Knowledge in the local enrichment area close to the crack tip in case of the original XFEM. On the other hand, it was shown that the Priori Knowledge can be accurately reproduced over the entire enrichment in the PUFEM-based XFEM.

Stefan V. Baumgartner - One of the best experts on this subject based on the ideXlab platform.

  • novel post doppler stap with a Priori Knowledge information for traffic monitoring applications basic idea and first results
    Advances in Radio Science, 2017
    Co-Authors: Andre Barros Cardoso Da Silva, Stefan V. Baumgartner
    Abstract:

    Abstract. This paper presents a novel a Priori Knowledge-based algorithm for traffic monitoring applications. The powerful post-Doppler space-time adaptive processing (PD STAP) is combined with a known road network obtained from the freely available OpenStreetMap (OSM) database. The road information is applied after the PD STAP for recognizing and rejecting false detections, and moreover, for repositioning the vehicles detected in the vicinity of the roads. The algorithm presents great potential for real-time processing, decreased hardware complexity and low costs compared to state-of-the-art systems. The processor was tested using real multi-channel data acquired by DLR's airborne system F-SAR. The experimental results are shown and discussed, and the novelties are highlighted (e.g., the benefits of using a Priori Knowledge information).

  • a Priori Knowledge based post doppler stap for traffic monitoring applications
    International Geoscience and Remote Sensing Symposium, 2012
    Co-Authors: Stefan V. Baumgartner, Gerhard Krieger
    Abstract:

    In this paper an extension of our “Fast GMTI Algorithm for Traffic Monitoring Based on A Priori Knowledge” [1,2] to an arbitrary number of M receiving (RX) channels is presented. This is done by incorporating Post-Doppler space-time adaptive processing into the processing chain. In contrast to our original dual-channel algorithm this additionally allows for robust estimation of the direction-of-arrival (DOA) angles of the detected signals. As a consequence false detections can be recognized and discarded. In the paper the processing chain is explained and performance estimation results for DLR's multi-channel airborne F-SAR system are presented and discussed.

  • Fast GMTI algorithm for traffic monitoring based on a Priori Knowledge
    IEEE Transactions on Geoscience and Remote Sensing, 2012
    Co-Authors: Stefan V. Baumgartner, Gerhard Krieger
    Abstract:

    In this paper, a fast a Priori Knowledge-based ground moving target indication and parameter estimation algorithm applicable to single- as well as to multichannel synthetic aperture airborne radar data is presented. The algorithm operates directly on range-compressed data. Only the intersection points of the moving vehicle signals with the a Priori known road axes, which are mapped into the range-compressed data array, are evaluated. For moving vehicle detection and parameter estimation, basically only a single 1-D fast Fourier transformation has to be performed for each considered road point. Hence, the required computational power is low, and the algorithm is well suited for real-time traffic monitoring applications. The proposed algorithm enables the estimation of the position and velocity vectors of detected moving vehicles independent of the number of channels. A single-channel synthetic aperture radar system may be sufficient in case of fast moving vehicles. The paper includes a detailed performance assessment together with experimental results that demonstrate the applicability in a real-world scenario.

  • real time road traffic monitoring using a fast a Priori Knowledge based sar gmti algorithm
    International Geoscience and Remote Sensing Symposium, 2010
    Co-Authors: Stefan V. Baumgartner, Gerhard Krieger
    Abstract:

    Radar systems operating on high altitude platforms can provide traffic information over wide areas, independent of sunlight illumination and weather conditions. In the paper, a novel a Priori Knowledge based ground moving target indication (GMTI) and parameter estimation algorithm applicable on single- as well as on multi-channel synthetic aperture radar (SAR) data is presented. Only the intersection points of the moving vehicle signals with the a Priori known road axes, which are mapped into the range-compressed data domain, are evaluated. The algorithm needs low computational load and is hence well suited for real-time traffic monitoring applications.

  • a Priori Knowledge based gmti algorithm for traffic monitoring applications
    Synthetic Aperture Radar (EUSAR) 2010 8th European Conference on, 2010
    Co-Authors: Stefan V. Baumgartner, Gerhard Krieger
    Abstract:

    In the paper a ground moving target indication and parameter estimation algorithm applicable on single- as well as on multi-channel synthetic aperture radar data is presented. The algorithm is based on a Priori Knowledge and operates directly on range-compressed data. Only the intersection points of the moving vehicle signals with the a Priori known road axes, which are mapped into the range-compressed data domain, are evaluated. The algorithm needs low computational power and hence, it is suitable for real time traffic monitoring applications. The absolute velocities, the headings and the geocoded positions of the detected moving vehicles can be estimated. A verification of the algorithm is done using real dual-channel data acquired with DLR's new airborne system F-SAR.