The Experts below are selected from a list of 4545 Experts worldwide ranked by ideXlab platform
Tomomichi Hagiwara - One of the best experts on this subject based on the ideXlab platform.
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brief h2 and h norm computations of linear continuous time periodic systems via the skew analysis of frequency response operators
Automatica, 2002Co-Authors: Jun Zhou, Tomomichi HagiwaraAbstract:The H"2 and H"~ norm computations of finite-dimensional linear continuous-time periodic (FDLCP) systems through the frequency response operators defined by steady-state analysis are discussed. By the skew truncation, the H"2 norm can be reached to any degree of accuracy by that of an asymptotically equivalent linear time-invariant (LTI) continuous-time system. The H"~ norm can be approximated by the maximum singular value of the frequency response of an asymptotically equivalent LTI continuous-time system over a certain frequency range via the modified skew truncation. By the latter result, a Hamiltonian test is proved for FDLCP systems in an LTI fashion, based on which a modified Bisection Algorithm is developed.
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corrections to Bisection Algorithm for computing the frequency response gain of sampled data systems infinite dimensional congruent transformation approach
IEEE Transactions on Automatic Control, 2001Co-Authors: Y Ito, Tomomichi Hagiwara, H Maeda, Mituhiko ArakiAbstract:This paper derives a Bisection Algorithm for computing the frequency response gain of sampled-data systems with their intersample behavior taken into account. The properties of the infinite-dimensional congruent transformation (i.e., the Schur complement arguments and the Sylvester law of inertia) play a key role in the derivation. Specifically, it is highlighted that counting up the numbers of the negative eigenvalues of self-adjoint operators is quite important for the computation of the frequency response gain. This contrasts with the well-known arguments on the related issue of the sampled-data H/sub /spl infin// problem, where the key role is played by the positivity of operators and the loop-shifting technique. The effectiveness of the derived Algorithm is demonstrated through a numerical example.
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H, Norm Computation of Contimioils-Time Periodic Systems -Asymptotic Hamiltonian Test and Modified Bisection Algorithm
2001Co-Authors: Jun Zhou, Tomomichi HagiwaraAbstract:In this paper, the computation of the H, norms of a class of finite-dimensional linear continuous-time periodic (FDLCP) systems is discussed. By a staircase truncation on the frequency response operators of FDLCP systems, asymptotic LTI continuous-time models are established, based on which the H, norms can be estimated in the asymptotic sense, and thus the Hamiltonian tcst is recovered in the FDLCP setting. From this asymptotic Hamiltonian test, a modified Bisection Algorithm is developed for the H, norm estimation. It is also considered to implement the Algorithm via approximate modeling, which is niimerically implementable in most practical FDLCP systems.
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further study on the Bisection Algorithm for the frequency response gain computation of sampled data systems and related issues
American Control Conference, 2000Co-Authors: Y Ito, Tomomichi Hagiwara, H Maeda, Mituhiko ArakiAbstract:The authors (1998), derived a sophisticated Bisection Algorithm for computing the frequency response gain of sampled-data systems with the lifting approach. In this paper, we first give an alternative Bisection method with the FR-operator approach, by applying the same fundamental technique as in the lifting case. Next, we clarify the relationship between the lifting-based Bisection method and the one-dimensional search method given by Yamamoto and Khargonekar (1996). We then study the computational aspects of the frequency response gain of sampled-data systems, by comparing these three methods through a numerical example.
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Bisection Algorithm for computing the frequency response gain of sampled data systems
Conference on Decision and Control, 1998Co-Authors: Y Ito, Tomomichi Hagiwara, H Maeda, M AraiAbstract:Presents a Bisection Algorithm for computing the frequency response gain of sampled-data systems composed of a continuous-time and a discrete-time system together with a sampler and a hold. Although a Bisection Algorithm is known in the literature, it is applicable only to those frequencies at which the frequency response gain is greater than /spl par/D/spl par/, where D, denotes the direct feed-through term in the lifted transfer function of the sampled-data system. The paper gives a new Bisection Algorithm that can be applied to any frequencies. The derivation given is based on the lifting technique, and the properties of the congruent transformation (the Schur complement and the Sylvester law of inertia) play a key role. To facilitate the Algorithm, a Bisection Algorithm for computing the singular values of D is also presented with the combined use of the lifting and FR-operator techniques.
Theodoros Tsiligkaridis - One of the best experts on this subject based on the ideXlab platform.
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active query driven visual search using probabilistic Bisection and convolutional neural networks
arXiv: Computer Vision and Pattern Recognition, 2018Co-Authors: Athanasios Tsiligkaridis, Theodoros TsiligkaridisAbstract:We present a novel efficient object detection and localization framework based on the probabilistic Bisection Algorithm. A Convolutional Neural Network (CNN) is trained and used as a noisy oracle that provides answers to input query images. The responses along with error probability estimates obtained from the CNN are used to update beliefs on the object location along each dimension. We show that querying along each dimension achieves the same lower bound on localization error as the joint query design. Finally, we compare our approach to the traditional sliding window technique on a real world face localization task and show speed improvements by at least an order of magnitude while maintaining accurate localization.
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distributed probabilistic Bisection search using social learning
International Conference on Acoustics Speech and Signal Processing, 2017Co-Authors: Athanasios Tsiligkaridis, Theodoros TsiligkaridisAbstract:We present a novel distributed probabilistic Bisection Algorithm using social learning with application to target localization. Each agent in the network first constructs a query about the target based on its local information and obtains a noisy response. Agents then perform a Bayesian update of their beliefs followed by an averaging of the log beliefs over local neighborhoods. This two stage Algorithm consisting of repeated querying and averaging runs until convergence. We derive bounds on the rate of convergence of the beliefs at the correct target location. Numerical simulations show that our method outperforms current state of the art methods.
Adrian Bekasiewicz - One of the best experts on this subject based on the ideXlab platform.
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em driven multi objective design of impedance transformers by pareto ranking Bisection Algorithm
2017 International Applied Computational Electromagnetics Society Symposium (ACES), 2017Co-Authors: Adrian Bekasiewicz, Slawomir Koziel, Qingsha S. Cheng, J W BandlerAbstract:In the paper, the problem of fast multi-objective optimization of compact impedance matching transformers is addressed by utilizing a novel Pareto ranking Bisection Algorithm. It approximates the Pareto front by dividing line segments connecting the designs found in the previous iterations, and refining the obtained candidate solutions by means of poll-type search involving Pareto ranking. The final Pareto set is obtained using surrogate-based optimization techniques. Our approach is validated using a compact impedance matching transformer and compared to state-of-the-art surrogate-assisted techniques.
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Pareto ranking Bisection Algorithm for rapid multi-objective design of antenna structures
2017 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization for RF Microwave and Terahertz Applic, 2017Co-Authors: Slawomir Koziel, Adrian Bekasiewicz, Qingsha S. Cheng, Qingfeng ZhangAbstract:In this paper, a novel technique for fast multi-objective design optimization of antenna structures has been presented. In our approach, the initial approximation of the Pareto front is obtained using a Bisection Algorithm which performs sequential partitioning of the design space and refines the new designs by means of poll-type search involving Pareto ranking. This stage of the optimization process is executed at the level of low-fidelity EM antenna model. The final Pareto set is found using surrogate-assisted techniques. The approach is demonstrated using a UWB monopole antenna.
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pareto ranking Bisection Algorithm for expedited multiobjective optimization of antenna structures
IEEE Antennas and Wireless Propagation Letters, 2017Co-Authors: Slawomir Koziel, Adrian BekasiewiczAbstract:The purpose of this letter is the introduction of a novel methodology for expedited multiobjective design of antenna structures. The key component of the presented approach is fast identification of the initial representation of the Pareto front (i.e., a set of design representing the best possible tradeoffs between conflicting objectives) using a Pareto-ranking Bisection Algorithm. The Algorithm finds a discrete set of Pareto-optimal designs. Its operation principle is sequential partitioning of the line segments connecting the designs found in the previous iterations, and refining the new designs allocated this way by means of poll-type search involving Pareto ranking. Subsequently, the final Pareto set is obtained by means of response correction techniques. Our methodology is demonstrated using an ultrawideband monopole antenna and compared to state-of-the-art multiobjective optimization methods.
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pareto ranking Bisection Algorithm for em driven multi objective design of antennas in highly dimensional parameter spaces
International Conference on Conceptual Structures, 2017Co-Authors: Slawomir Koziel, Adrian Bekasiewicz, Leifur LeifssonAbstract:Abstract A deterministic technique for fast surrogate-assisted multi-objective design optimization of antennas in highly-dimensional parameters spaces has been discussed. In this two-stage approach, the initial approximation of the Pareto set representing the best compromise between conflicting objectives is obtained using a Bisection Algorithm which finds new Pareto-optimal designs by dividing the line segments interconnecting previously found optimal points, and executing poll-type search that involves Pareto ranking. The initial Pareto front is generated at the level of the coarsely-discretized EM model of the antenna. In the second stage of the Algorithm, the high-fidelity Pareto designs are obtained through optimization of corrected local-approximation models. The considered optimization method is verified using a 17-variable uniplanar antenna operating in ultra-wideband frequency range. The method is compared to three state-of-the-art surrogate-assisted multi-objective optimization Algorithms.
Dirk Roose - One of the best experts on this subject based on the ideXlab platform.
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an improved spectral Bisection Algorithm and its application to dynamic load balancing
Parallel Computing, 1995Co-Authors: R Van Driessche, Dirk RooseAbstract:Abstract The efficient parallel execution of grid-oriented scientific calculations requires a partitioning of the grid that minimises both load imbalance and interprocessor communication. For unstructured static grids, good partitions are obtained with the recursive spectral Bisection heuristic, applied to the interdependency graph of the grid. We will describe an alternative spectral Bisection Algorithm that yields better partitions than the standard Algorithm, especially for interdependency graphs with a large variation in the weights of the edges. We will further describe how even in case of dynamically changing grids, grid-oriented problems can be formulated as graph partitioning problems for the purpose of load balancing. We will then partition these dynamically changing grids with the alternative spectral Algorithm.
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dynamic load balancing with a spectral Bisection Algorithm for the constrained graph partitioning problem
Lecture Notes in Computer Science, 1995Co-Authors: Raf Van Driessche, Dirk RooseAbstract:We present a spectral Bisection Algorithm for the constrained graph partitioning problem, i.e. a graph partitioning problem in which some of the vertices of the graph are assigned a priori to given subsets. We show how this Algorithm can be used for dynamic load balancing of grid-oriented problems on dynamically changing grids.
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dynamic load balancing with an improved with an improved spectral Bisection Algorithm
IEEE International Conference on High Performance Computing Data and Analytics, 1994Co-Authors: Raf Van Driessche, Dirk RooseAbstract:The efficient parallel execution of grid-oriented scientific calculations requires the partitioning of the grid in such a way that the work load is equally distributed over the processors of the parallel machine and that communication among the processors is minimized. For unstructured static grids, good partitions are obtained by applying the recursive spectral Bisection heuristic to the interdependency graph of the grid. We describe how even in case of dynamically changing grids, grid-oriented problems can be formulated as graph partitioning problems for the purpose of load balancing. We further describe an alternative spectral Bisection Algorithm that yields better partitions than the standard Algorithm for the graphs that model dynamic load balancing problems. >
Mituhiko Araki - One of the best experts on this subject based on the ideXlab platform.
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corrections to Bisection Algorithm for computing the frequency response gain of sampled data systems infinite dimensional congruent transformation approach
IEEE Transactions on Automatic Control, 2001Co-Authors: Y Ito, Tomomichi Hagiwara, H Maeda, Mituhiko ArakiAbstract:This paper derives a Bisection Algorithm for computing the frequency response gain of sampled-data systems with their intersample behavior taken into account. The properties of the infinite-dimensional congruent transformation (i.e., the Schur complement arguments and the Sylvester law of inertia) play a key role in the derivation. Specifically, it is highlighted that counting up the numbers of the negative eigenvalues of self-adjoint operators is quite important for the computation of the frequency response gain. This contrasts with the well-known arguments on the related issue of the sampled-data H/sub /spl infin// problem, where the key role is played by the positivity of operators and the loop-shifting technique. The effectiveness of the derived Algorithm is demonstrated through a numerical example.
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further study on the Bisection Algorithm for the frequency response gain computation of sampled data systems and related issues
American Control Conference, 2000Co-Authors: Y Ito, Tomomichi Hagiwara, H Maeda, Mituhiko ArakiAbstract:The authors (1998), derived a sophisticated Bisection Algorithm for computing the frequency response gain of sampled-data systems with the lifting approach. In this paper, we first give an alternative Bisection method with the FR-operator approach, by applying the same fundamental technique as in the lifting case. Next, we clarify the relationship between the lifting-based Bisection method and the one-dimensional search method given by Yamamoto and Khargonekar (1996). We then study the computational aspects of the frequency response gain of sampled-data systems, by comparing these three methods through a numerical example.