The Experts below are selected from a list of 12309 Experts worldwide ranked by ideXlab platform

Moritz Diehl - One of the best experts on this subject based on the ideXlab platform.

  • A Relaxation Strategy for the optimization of Airborne Wind Energy systems
    2013 European Control Conference (ECC), 2013
    Co-Authors: Sébastien Gros, M. Zanon, Moritz Diehl
    Abstract:

    Optimal control is recognized by the Airborne Wind Energy (AWE) community as a crucial tool for the development of the AWE industry. More specifically, the optimization of AWE systems for power generation is required to achieve the performance needed for their industrial viability. Models for AWE systems are highly nonlinear coupled systems. As a result, the optimization of power generation based on Newton-type techniques requires a very good initial guess. Such initial guess, however, is generally not available. To tackle this issue, this paper proposes a homotopy Strategy based on the Relaxation of the dynamic constraints of the optimization problem. The relaxed problem differs from the original one only by a single parameter, which is gradually modified to obtain the solution to the original problem.

  • ECC - A Relaxation Strategy for the optimization of Airborne Wind Energy systems
    2013 European Control Conference (ECC), 2013
    Co-Authors: Sébastien Gros, M. Zanon, Moritz Diehl
    Abstract:

    Optimal control is recognized by the Airborne Wind Energy (AWE) community as a crucial tool for the development of the AWE industry. More specifically, the optimization of AWE systems for power generation is required to achieve the performance needed for their industrial viability. Models for AWE systems are highly nonlinear coupled systems. As a result, the optimization of power generation based on Newton-type techniques requires a very good initial guess. Such initial guess, however, is generally not available. To tackle this issue, this paper proposes a homotopy Strategy based on the Relaxation of the dynamic constraints of the optimization problem. The relaxed problem differs from the original one only by a single parameter, which is gradually modified to obtain the solution to the original problem.

Rémi Gribonval - One of the best experts on this subject based on the ideXlab platform.

  • Compressed sensing with unknown sensor permutation
    2014
    Co-Authors: Valentin Emiya, Antoine Bonnefoy, Laurent Daudet, Rémi Gribonval
    Abstract:

    Compressed sensing is the ability to retrieve a sparse vector from a set of linear measurements. The task gets more difficult when the sensing process is not perfectly known. We address such a problem in the case where the sensors have been permuted, i.e., the order of the measurements is unknown. We propose a branch-and-bound algorithm that converges to the solution. The experimental study shows that our approach always retrieves the unknown permutation, while a simple convex Relaxation Strategy almost always fails. In terms of its time complexity, we show that the proposed algorithm converges quickly with respect to the combinatorial nature of the problem.

  • ICASSP - Compressed sensing with unknown sensor permutation
    2014 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2014
    Co-Authors: Valentin Emiya, Antoine Bonnefoy, Laurent Daudet, Rémi Gribonval
    Abstract:

    Compressed sensing is the ability to retrieve a sparse vector from a set of linear measurements. The task gets more difficult when the sensing process is not perfectly known. We address such a problem in the case where the sensors have been permuted, i.e., the order of the measurements is unknown. We propose a branch-and-bound algorithm that converges to the solution. The experimental study shows that our approach always retrieves the unknown permutation, while a simple convex Relaxation Strategy almost always fails. In terms of its time complexity, we show that the proposed algorithm converges quickly with respect to the combinatorial nature of the problem.

B. Yegnanarayana - One of the best experts on this subject based on the ideXlab platform.

  • Supervised texture classification using a probabilistic neural network and constraint satisfaction model
    IEEE transactions on neural networks, 1998
    Co-Authors: P.p. Raghu, B. Yegnanarayana
    Abstract:

    The texture classification problem is projected as a constraint satisfaction problem. The focus is on the use of a probabilistic neural network (PNN) for representing the distribution of feature vectors of each texture class in order to generate a feature-label interaction constraint. This distribution of features for each class is assumed as a Gaussian mixture model. The feature-label interactions and a set of label-label interactions are represented on a constraint satisfaction neural network. A stochastic Relaxation Strategy is used to obtain an optimal classification of textures in an image. The advantage of this approach is that all classes in an image are determined simultaneously, similar to human perception of textures in an image.

  • ICNN - Texture classification using a probabilistic neural network and constraint satisfaction model
    Proceedings of International Conference on Neural Networks (ICNN'96), 1
    Co-Authors: P.p. Raghu, B. Yegnanarayana
    Abstract:

    In this paper, the texture classification problem is projected as a constraint satisfaction problem. The focus is on the use of a probabilistic neural network for representing the distribution of feature vectors of each texture class in order to generate a feature-label interaction constraint. This distribution is assumed as a Gaussian mixture model. The feature-label interactions and a set of label-label interactions are represented on a constraint satisfaction neural network. A stochastic Relaxation Strategy is used to obtain an optimal classification of the textured image.

Sébastien Gros - One of the best experts on this subject based on the ideXlab platform.

  • A Relaxation Strategy for the optimization of Airborne Wind Energy systems
    2013 European Control Conference (ECC), 2013
    Co-Authors: Sébastien Gros, M. Zanon, Moritz Diehl
    Abstract:

    Optimal control is recognized by the Airborne Wind Energy (AWE) community as a crucial tool for the development of the AWE industry. More specifically, the optimization of AWE systems for power generation is required to achieve the performance needed for their industrial viability. Models for AWE systems are highly nonlinear coupled systems. As a result, the optimization of power generation based on Newton-type techniques requires a very good initial guess. Such initial guess, however, is generally not available. To tackle this issue, this paper proposes a homotopy Strategy based on the Relaxation of the dynamic constraints of the optimization problem. The relaxed problem differs from the original one only by a single parameter, which is gradually modified to obtain the solution to the original problem.

  • ECC - A Relaxation Strategy for the optimization of Airborne Wind Energy systems
    2013 European Control Conference (ECC), 2013
    Co-Authors: Sébastien Gros, M. Zanon, Moritz Diehl
    Abstract:

    Optimal control is recognized by the Airborne Wind Energy (AWE) community as a crucial tool for the development of the AWE industry. More specifically, the optimization of AWE systems for power generation is required to achieve the performance needed for their industrial viability. Models for AWE systems are highly nonlinear coupled systems. As a result, the optimization of power generation based on Newton-type techniques requires a very good initial guess. Such initial guess, however, is generally not available. To tackle this issue, this paper proposes a homotopy Strategy based on the Relaxation of the dynamic constraints of the optimization problem. The relaxed problem differs from the original one only by a single parameter, which is gradually modified to obtain the solution to the original problem.

Chao Wang - One of the best experts on this subject based on the ideXlab platform.

  • an ill posed optimization method and Relaxation Strategy of landweber for emt system based on tmr
    The Journal of Thoracic and Cardiovascular Surgery, 2020
    Co-Authors: Qi Guo, Chao Wang
    Abstract:

    The sensitivity matrix of Electromagnetic Tomography (EMT) system based on Tunneling Magneto Resistance (TMR) has the characteristics of high sensitivity only near the TMR and low sensitivity at other positions, which leads to more serious ill-posed problem of image reconstruction. Focusing on the ill-posed problem, an appropriate weight matrix and Relaxation Strategy to optimize the Landweber method is proposed in this paper. By verifying the consistency of the condition number and spectral radius of iterative matrix, a weight matrix is introduced to improve the condition number. Then, based on the principle of minimizing the spectral radius of the newly derived iterative matrix, an optimal Relaxation factor is determined for the optimized Landweber. Compared the new approach with Landweber with a constant Relaxation factor 1, the results show that the average correlation coefficient (CC) of the optimized Landweber for the four models is 0.8260, which is much higher than the 0.6525 of Landweber with a constant Relaxation factor. Meanwhile, the convergence analysis of the two algorithms indicates that the new approach can solve the semi-convergence problem of Landweber.

  • I2MTC - An Ill-posed Optimization Method and Relaxation Strategy of Landweber for EMT System Based on TMR
    2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2020
    Co-Authors: Qi Guo, Chao Wang
    Abstract:

    The sensitivity matrix of Electromagnetic Tomography (EMT) system based on Tunneling Magneto Resistance (TMR) has the characteristics of high sensitivity only near the TMR and low sensitivity at other positions, which leads to more serious ill-posed problem of image reconstruction. Focusing on the ill-posed problem, an appropriate weight matrix and Relaxation Strategy to optimize the Landweber method is proposed in this paper. By verifying the consistency of the condition number and spectral radius of iterative matrix, a weight matrix is introduced to improve the condition number. Then, based on the principle of minimizing the spectral radius of the newly derived iterative matrix, an optimal Relaxation factor is determined for the optimized Landweber. Compared the new approach with Landweber with a constant Relaxation factor 1, the results show that the average correlation coefficient (CC) of the optimized Landweber for the four models is 0.8260, which is much higher than the 0.6525 of Landweber with a constant Relaxation factor. Meanwhile, the convergence analysis of the two algorithms indicates that the new approach can solve the semi-convergence problem of Landweber.

  • SOFSEM - Decomposable Relaxation for Concurrent Data Structures
    SOFSEM 2017: Theory and Practice of Computer Science, 2017
    Co-Authors: Chao Wang
    Abstract:

    We propose a Relaxation scheme for defining specifications of relaxed data structures. It can produce a relaxed specification parameterized with a specification of a standard data structure, a transition cost function and a Relaxation Strategy represented by a finite automaton. We show that this Relaxation scheme can cover the known specifications of typical relaxed queues and stacks.