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Multiple time scale decomposition
, 1988
"... Abstract: 'Pae multiple time scale decomposition of discrete time, finite state Markov chains is addressed. In [1, 2], the behavior of a continuous time Markov chain is approximated using a fast time scale, eindependent, continuous time process, and a reduced order perturbed process. The proce ..."
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Abstract: 'Pae multiple time scale decomposition of discrete time, finite state Markov chains is addressed. In [1, 2], the behavior of a continuous time Markov chain is approximated using a fast time scale, eindependent, continuous time process, and a reduced order perturbed process
Multiple Time Scales
"... Variational Integrators [Marsden and West (2001)] approximate the Lagrangian of a mechanical system, then use a variational principle to derive a structurepreserving numerical scheme. However, as originally formulated, they require imposing a uniform time step size on all components of the system, ..."
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, which may not be desirable for certain kinds of problems with multiple time scales. Asynchronous Variational Integrators [Lew et. al (2003)] (AVIs) solve this difficulty for problems like elastodynamics, where the Lagrangian can be decomposed into contributions from different spatial elements. One can
RCBR: A Simple and Efficient Service for Multiple TimeScale Traffic
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 1997
"... Variable bitrate (VBR) compressed video traffic is expected to be a significant component of the traffic mix in integrated services networks. This traffic is hard to manage because it has strict delay and loss requirements while simultaneously exhibiting burstiness at multiple time scales. We show ..."
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Cited by 169 (4 self)
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Variable bitrate (VBR) compressed video traffic is expected to be a significant component of the traffic mix in integrated services networks. This traffic is hard to manage because it has strict delay and loss requirements while simultaneously exhibiting burstiness at multiple time scales. We show
Learning to Control at Multiple Time Scales
 Artificial Neural Networks and Neural Information Processing  ICANN/ICONIP 2003, Joint International Conference ICANN/ICONIP 2003
, 2003
"... In reinforcement learning the interaction between the agent and the environment generally takes place on a xed time scale, which means that the control interval is set to a xed time step. In order to determine a suitable xed time scale one has to trade o accuracy in control against learning c ..."
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Cited by 2 (0 self)
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complexity. In this paper we present an alternative approach that enables the agent to learn a control policy by using multiple time scales simultaneously. Instead of preselecting a xed time scale, there are several time scales available during learning and the agent can select the appropriate time
Corrigenda to ”‘Multiple Time Scale Dynamics”
, 2015
"... This document is going to collect corrigenda to the book [2]. In particular, typographical and similar errors will be marked in blue while (hopefully not many) mathematical errors will be labelled red. Unfortunately, the existence problem for errors is not very pleasent, e.g., suppose each page is ..."
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This document is going to collect corrigenda to the book [2]. In particular, typographical and similar errors will be marked in blue while (hopefully not many) mathematical errors will be labelled red. Unfortunately, the existence problem for errors is not very pleasent, e.g., suppose each page is correct with 99% probability and we take a rough page count at 800 pages total then P(“no errors at all”) = (0.99)800 ≈ 3 · 10−4 or otherwise said: the probability of no errors in the entire book would be approximately 0.03%. Hence, the existence of this document is unfortunately necessary. Please send me any errors or typos you find and I am going to include them here; please make sure you know precisely how a correct version should read to avoid false alarms. • p.229,(8.67): The first equality should be an inequality ∂
Statistical Multiplexing of Multiple TimeScale Markov Streams
 IEEE JSAC, SPECIAL ISSUE ON ADVANCES IN THE FUNDAMENTALS OF NETWORKING
, 1995
"... We study the problem of statistical multiplexing of cell streams that have correlations at multiple timescales. Each stream is modeled by a singularly perturbed Markovmodulated process with some state transitions occurring much less frequently than others. One motivation of this model comes from v ..."
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Cited by 38 (2 self)
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We study the problem of statistical multiplexing of cell streams that have correlations at multiple timescales. Each stream is modeled by a singularly perturbed Markovmodulated process with some state transitions occurring much less frequently than others. One motivation of this model comes from
Mixedmode oscillations with multiple time scales
 SIAM REV
, 2012
"... Mixedmode oscillations (MMOs) are trajectories of a dynamical system in which there is an alternation between oscillations of distinct large and small amplitudes. MMOs have been observed and studied for over thirty years in chemical, physical, and biological systems. Few attempts have been made t ..."
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Cited by 34 (17 self)
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thus far to classify different patterns of MMOs, in contrast to the classification of the related phenomena of bursting oscillations. This paper gives a survey of different types of MMOs, concentrating its analysis on MMOs whose smallamplitude oscillations are produced by a local, multipletimescale
Hierarchical aggregation of linear systems with multiple time scales
 IEEE Trans. Auto. Contr
, 1983
"... AbstrucfIn this paper we carry out a detailed analysis of the multiple time scale behavior of singularly perturbed linear systems of the form.kc ( t) = A ( 6) If ( t) where A(<) is analytic in the small parameter e. Our basic result is a uniform asymptotic approximation to exp A ( e)r that we o ..."
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Cited by 11 (3 self)
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AbstrucfIn this paper we carry out a detailed analysis of the multiple time scale behavior of singularly perturbed linear systems of the form.kc ( t) = A ( 6) If ( t) where A(<) is analytic in the small parameter e. Our basic result is a uniform asymptotic approximation to exp A ( e)r that we
Multiple Time Scales and Subexponentiality in MPEG Video Streams
 in International IFIPIEEE Conference on Broadband Communications
, 1996
"... We develop a practical, multiple time scale model for MPEG video traffic whose accuracy and relatively low computational complexity make it well suited for realtime traffic generation experiments on broadband networks. The major feature of our approach is the decomposition of the frame size sequenc ..."
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Cited by 23 (10 self)
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We develop a practical, multiple time scale model for MPEG video traffic whose accuracy and relatively low computational complexity make it well suited for realtime traffic generation experiments on broadband networks. The major feature of our approach is the decomposition of the frame size
Geometric Structure Of Multiple TimeScale Nonlinear Systems
 Proceedings of the 14th World Congress, Vol. 5, International Federation of Automatic Control, Laxenburg
, 1999
"... : The geometric structure of #nitedimensional nonlinear systems with dynamics on multiple timescales is studied by analyzing the timescale structure present in the associated linear variational system whichevolves on the tangent bundle to the statespace. As a #rst step, we restrict our attent ..."
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Cited by 1 (1 self)
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: The geometric structure of #nitedimensional nonlinear systems with dynamics on multiple timescales is studied by analyzing the timescale structure present in the associated linear variational system whichevolves on the tangent bundle to the statespace. As a #rst step, we restrict our
Results 1  10
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