The Experts below are selected from a list of 1210242 Experts worldwide ranked by ideXlab platform
Oded Maimon - One of the best experts on this subject based on the ideXlab platform.
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Effective Information horizon length in measuring off-line performance of stochastic dynamic systems
European Journal of Operational Research, 2004Co-Authors: A. Herbon, E. Khmelnitsky, Oded MaimonAbstract:Abstract In stochastic problems, several sources of complete (deterministic) and incomplete (stochastic) Information become available in the course of time. In this paper we introduce a `pseudo-stochastic' approach, which allows modeling a specific distribution of the event's occurrence time. This model shows the possible impact of Future Information that is expected beyond the planning horizon, on the off-line evaluation of a dynamic system performance. By not considering the expected Information beyond the planning horizon, one obtains a non-accurate performance measure of the system. Since the computational time for performance evaluation increases with the increase of the amount of Future Information, and since long-range forecasts are usually not accurate, we develop an analytic procedure to reduce the amount of required Information. In this paper we introduce a new concept––the effective Information horizon (EIH)––that measures the segment of time on which Future stochastic Information is relevant for evaluating the system's performance. The EIH length is found by mathematical analysis of the influence of Future Information on a system's dynamics under a given control strategy. Although real-life examples show that the EIH is larger than the planning horizon, it is quite limited.
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Reduction of Future Information required for optimal control of dynamic systems: a pseudostochastic model
IEEE Transactions on Automatic Control, 2003Co-Authors: A. Herbon, E. Khmelnitsky, Oded Maimon, Y. YakubovAbstract:This note develops a pseudostochastic model for optimal control of dynamic systems over a given planning horizon. The obtained results reflect the extent to which reduction of Future Information impacts upon the performance and optimal control of dynamic systems. The main results indicate that, when using only partial Information for determining optimal control, the performance of the dynamic system is almost identical to that when using full Information. When ignoring the Information expected beyond the planning horizon, a significant performance loss and a possible violation of feasibility of the optimal control can occur.
Tsuen-wan Johnny Ngan - One of the best experts on this subject based on the ideXlab platform.
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Extra Processors versus Future Information in Optimal Deadline Scheduling
Theory of Computing Systems, 2004Co-Authors: Chiu-yuen Koo, Tak-wah Lam, Tsuen-wan Johnny NganAbstract:This paper is concerned with the design of online scheduling algorithms that exploit extra resources. In particular, it studies how to make use of multiple processors to counteract the lack of Future Information in online deadline scheduling. Our results extend the previous work that are primarily based on using a faster processor to obtain a performance guarantee. The challenge arises from the fact that jobs are sequential in nature and cannot be executed on more than one processor at the same time. Thus, a faster processor can speed up a job while multiple unit-speed processors cannot.
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SPAA - Extra processors versus Future Information in optimal deadline scheduling
Proceedings of the fourteenth annual ACM symposium on Parallel algorithms and architectures - SPAA '02, 2002Co-Authors: Chiu-yuen Koo, Tak-wah Lam, Tsuen-wan Johnny NganAbstract:This paper is concerned with the extra-resource analysis of online scheduling algorithms. In particular, it studies how to make use of multiple processors to counteract the lack of Future Information in online deadline scheduling. Our results extend the previous work that are primarily based on using a faster processor to obtain a performance guarantee. The challenge arises from the fact that jobs are sequential in nature and cannot be executed on more than one processor at the same time. Thus, a faster processor can speed up a job while multiple unit-speed processors cannot help.
Yasuo Takahashi - One of the best experts on this subject based on the ideXlab platform.
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manipulation and detection of single electrons for Future Information processing
Journal of Applied Physics, 2005Co-Authors: Yukinori Ono, Akira Fujiwara, Katsuhiko Nishiguchi, Hiroshi Inokawa, Yasuo TakahashiAbstract:The ultimate goal of Future Information processing might be the realization of a circuit in which one bit is represented by a single electron. Such a challenging circuit would comprise elemental devices whose tasks are to drag, transfer, and detect single electrons. In achieving these tasks, the Coulomb blockade, which occurs in tiny conducting materials, plays an important role. This paper describes the current status of research on such single-charge-control devices from the viewpoints of circuit applications.
Naftali Tishby - One of the best experts on this subject based on the ideXlab platform.
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Past-Future Information bottleneck in dynamical systems.
Physical Review E, 2009Co-Authors: Felix Creutzig, Amir Globerson, Naftali TishbyAbstract:Biological systems need to process Information in real time and must trade off accuracy of presentation and coding costs. Here we operationalize this trade-off and develop an Information-theoretic framework that selectively extracts Information of the input past that is predictive about the output Future, obtaining a generalized eigenvalue problem. Thereby, we unravel the input history in terms of structural phase transitions corresponding to additional dimensions of a state space. We elucidate the relation to canonical correlation analysis and give a numerical example. Altogether, this work relates Information-theoretic optimization to the joint problem of system identification and model reduction.
A. Herbon - One of the best experts on this subject based on the ideXlab platform.
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Effective Information horizon length in measuring off-line performance of stochastic dynamic systems
European Journal of Operational Research, 2004Co-Authors: A. Herbon, E. Khmelnitsky, Oded MaimonAbstract:Abstract In stochastic problems, several sources of complete (deterministic) and incomplete (stochastic) Information become available in the course of time. In this paper we introduce a `pseudo-stochastic' approach, which allows modeling a specific distribution of the event's occurrence time. This model shows the possible impact of Future Information that is expected beyond the planning horizon, on the off-line evaluation of a dynamic system performance. By not considering the expected Information beyond the planning horizon, one obtains a non-accurate performance measure of the system. Since the computational time for performance evaluation increases with the increase of the amount of Future Information, and since long-range forecasts are usually not accurate, we develop an analytic procedure to reduce the amount of required Information. In this paper we introduce a new concept––the effective Information horizon (EIH)––that measures the segment of time on which Future stochastic Information is relevant for evaluating the system's performance. The EIH length is found by mathematical analysis of the influence of Future Information on a system's dynamics under a given control strategy. Although real-life examples show that the EIH is larger than the planning horizon, it is quite limited.
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Reduction of Future Information required for optimal control of dynamic systems: a pseudostochastic model
IEEE Transactions on Automatic Control, 2003Co-Authors: A. Herbon, E. Khmelnitsky, Oded Maimon, Y. YakubovAbstract:This note develops a pseudostochastic model for optimal control of dynamic systems over a given planning horizon. The obtained results reflect the extent to which reduction of Future Information impacts upon the performance and optimal control of dynamic systems. The main results indicate that, when using only partial Information for determining optimal control, the performance of the dynamic system is almost identical to that when using full Information. When ignoring the Information expected beyond the planning horizon, a significant performance loss and a possible violation of feasibility of the optimal control can occur.
