Electrical and Electronic Engineering - Research Publications

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2005 - 2010 22
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Subject: Artificial Intelligence and Image Processing × Type: Journal Article ×

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Now showing 1 - 10 of 22
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    An information-based approach to sensor management in large dynamic networks
    Kreucher, CM ; Hero, AO ; Kastella, KD ; Morelande, MR (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2007-05-01)
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    Feedback control under data rate constraints: An overview
    Nair, GN ; Fagnani, F ; Zampieri, S ; Evans, RJ (INSTITUTE OF ELECTRICAL ELECTRONICS ENGINEERS (IEEE), 2007)
    The emerging area of control with limited data rates incorporates ideas from both control and information theory. The data rate constraint introduces quantization into the feedback loop and gives the interconnected system a two-fold nature, continuous and symbolic. In this paper, we review the results available in the literature on data-rate-limited control. For linear systems, we show how fundamental tradeoffs between the data rate and control goals, such as stability, mean entry times, and asymptotic state norms, emerge naturally. While many classical tools from both control and information theory can still be used in this context, it turns out that the deepest results necessitate a novel, integrated view of both disciplines.
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    Control of large-scale irrigation networks
    Cantoni, M ; Weyer, E ; Li, Y ; Ooi, SK ; Mareels, I ; Ryan, M (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2007-01-01)
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    Dynamically adjustable contrast enhancement from cortical background activity
    Meffin, H ; Burkitt, AN ; Grayden, DB (ELSEVIER, 2005-06-01)
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    License plate localization based on a probabilistic model
    Al-Hmouz, R ; Challa, S (SPRINGER, 2010-04-01)
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    Very high speed, close field, object positioning using tri-linear CCDs
    Jahshan, D ; Bredenfeld, A ; Jacoff, A ; Noda, I ; Takahashi, Y (SPRINGER-VERLAG BERLIN, 2006-01-01)
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    Interacting slow and fast dynamics in precise spiking-bursting neurons
    Baroni, F ; Torres, JJ ; Varona, P ; Mira, J ; Alvarez, JR (SPRINGER-VERLAG BERLIN, 2005-01-01)
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    Value Function Based Reinforcement Learning in Changing Markovian Environments
    Csaji, BC ; Monostori, L (MICROTOME PUBL, 2008-08-01)
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    Adaptive stochastic resource control: A machine learning approach
    Csaji, BC ; Monostori, L (AI ACCESS FOUNDATION, 2008-01-01)
    The paper investigates stochastic resource allocation problems with scarce, reusable resources and non-preemtive, time-dependent, interconnected tasks. This approach is a natural generalization of several standard resource management problems, such as scheduling and transportation problems. First, reactive solutions are considered and defined as control policies of suitably reformulated Markov decision processes (MDPs). We argue that this reformulation has several favorable properties, such as it has finite state and action spaces, it is aperiodic, hence all policies are proper and the space of control policies can be safely restricted. Next, approximate dynamic programming (ADP) methods, such as fitted Q-learning, are suggested for computing an efficient control policy. In order to compactly maintain the cost-to-go function, two representations are studied: hash tables and support vector regression (SVR), particularly, nu-SVRs. Several additional improvements, such as the application of limited-lookahead rollout algorithms in the initial phases, action space decomposition, task clustering and distributed sampling are investigated, too. Finally, experimental results on both benchmark and industry-related data are presented.