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3,740
Past Input Reconstruction in Fast LeastSquares Algorithms
, 1997
"... ... computed variables in a fast leastsquares prediction algorithm, determine all past input sequences that would have given rise to the variables in question. This problem is motivated by the backward consistency approach to numerical stability in this algorithm class; the set of reachable variabl ..."
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Cited by 1 (0 self)
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... computed variables in a fast leastsquares prediction algorithm, determine all past input sequences that would have given rise to the variables in question. This problem is motivated by the backward consistency approach to numerical stability in this algorithm class; the set of reachable
PAST INPUT RECONSTRUCTION IN BACKWARD CONSISTENT FAST LEASTSQUARES ALGORITHMS
"... We present an analytic solution to the past input reconstruction problem, which consists in describing all past input sequences which would give rise to a given set of variables in fast leastsquares algorithms, whenever the variables in question are reachable. 1 ..."
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We present an analytic solution to the past input reconstruction problem, which consists in describing all past input sequences which would give rise to a given set of variables in fast leastsquares algorithms, whenever the variables in question are reachable. 1
Data Streams: Algorithms and Applications
, 2005
"... In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerg ..."
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Cited by 533 (22 self)
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In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has
RealTime Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
"... A key challenge for neural modeling is to explain how a continuous stream of multimodal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrateandfire neurons in realtime. We propose a new computational model for realtime computing on timevar ..."
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Cited by 469 (38 self)
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time from the current state of such recurrent neural circuit information about current and past inputs that may be needed for diverse tasks. Stable internal states are not required for giving a stable output, since transient internal states can be transformed by readout neurons into stable target outputs
Multivariable Feedback Control: Analysis
 span (B∗) und Basis B∗ = { ω1
, 2005
"... multiinput, multioutput feedback control design for linear systems using the paradigms, theory, and tools of robust control that have arisen during the past two decades. The book is aimed at graduate students and practicing engineers who have a basic knowledge of classical control design and st ..."
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Cited by 564 (24 self)
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multiinput, multioutput feedback control design for linear systems using the paradigms, theory, and tools of robust control that have arisen during the past two decades. The book is aimed at graduate students and practicing engineers who have a basic knowledge of classical control design
Mental Accounting Matters
 JOURNAL OF BEHAVIORAL DECISION MAKING J. BEHAV. DEC. MAKING, 12: 183~206 (1999)
, 1999
"... Mental accounting is the set of cognitive operations used by individuals and households to organize, evaluate, and keep track of financial activities. Making use of research on this topic over the past decade, this paper summarizes the current state of our knowledge about how people engage in mental ..."
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Cited by 378 (6 self)
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Mental accounting is the set of cognitive operations used by individuals and households to organize, evaluate, and keep track of financial activities. Making use of research on this topic over the past decade, this paper summarizes the current state of our knowledge about how people engage
Lockupfree instruction fetch/prefetch cache organization
 In Proceedings of the 8th Annual International Symposium on Computer Architecture
, 1981
"... ABSTRACT In the past decade. there has been much literature describing various cache organizatrons that exploit general programming idiosyncrasies to obtain maxrmum hit rate (the probability that a requested datum is now resident in the cache). Little. if any, has been presented to exploit: (1) the ..."
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Cited by 365 (0 self)
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ABSTRACT In the past decade. there has been much literature describing various cache organizatrons that exploit general programming idiosyncrasies to obtain maxrmum hit rate (the probability that a requested datum is now resident in the cache). Little. if any, has been presented to exploit: (1
Sampling—50 years after Shannon
 Proceedings of the IEEE
, 2000
"... This paper presents an account of the current state of sampling, 50 years after Shannon’s formulation of the sampling theorem. The emphasis is on regular sampling, where the grid is uniform. This topic has benefited from a strong research revival during the past few years, thanks in part to the math ..."
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Cited by 339 (27 self)
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This paper presents an account of the current state of sampling, 50 years after Shannon’s formulation of the sampling theorem. The emphasis is on regular sampling, where the grid is uniform. This topic has benefited from a strong research revival during the past few years, thanks in part
On Characterizations of the InputtoState Stability Property
 SYSTEMS CONTROL LETTERS
, 1995
"... We show that the wellknown Lyapunov sufficient condition for "inputtostate stability" is also necessary, settling positively an open question raised by several authors during the past few years. Additional characterizations of the ISS property, including one in terms of nonlinear stabil ..."
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Cited by 225 (32 self)
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We show that the wellknown Lyapunov sufficient condition for "inputtostate stability" is also necessary, settling positively an open question raised by several authors during the past few years. Additional characterizations of the ISS property, including one in terms of nonlinear
Neuronal oscillations in cortical networks.
, 2004
"... Clocks tick, bridges and skyscrapers vibrate, neuronal networks oscillate. Are neuronal oscillations an inevitable byproduct, similar to bridge vibrations, or an essential part of the brain's design? Mammalian cortical neurons form behaviordependent oscillating networks of various sizes, whi ..."
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Cited by 311 (1 self)
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, which span five orders of magnitude in frequency. These oscillations are phylogenetically preserved, suggesting that they are functionally relevant. Recent findings indicate that network oscillations bias input selection, temporally link neurons into assemblies, and facilitate synaptic plasticity
Results 1  10
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