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» Modeling microstructure noise using Hawkes processes
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KES
2010
Springer
14 years 8 months ago
Evolving takagi sugeno modelling with memory for slow processes
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with lo...
Simon McDonald, Plamen P. Angelov
AUTOMATICA
2006
132views more  AUTOMATICA 2006»
14 years 9 months ago
A new autocovariance least-squares method for estimating noise covariances
Industrial implementation of model-based control methods, such as model predictive control, is often complicated by the lack of knowledge about the disturbances entering the syste...
Brian J. Odelson, Murali R. Rajamani, James B. Raw...
SOCO
2002
Springer
14 years 9 months ago
A dynamically-constructed fuzzy neural controller for direct model reference adaptive control of multi-input-multi-output nonlin
Conventional industrial control systems are in majority based on the single-input-single-output design principle with linearized models of the processes. However, most industrial p...
Yakov Frayman, Lipo Wang
70
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ICS
2005
Tsinghua U.
15 years 3 months ago
System noise, OS clock ticks, and fine-grained parallel applications
As parallel jobs get bigger in size and finer in granularity, “system noise” is increasingly becoming a problem. In fact, fine-grained jobs on clusters with thousands of SMP...
Dan Tsafrir, Yoav Etsion, Dror G. Feitelson, Scott...
ALT
1999
Springer
15 years 1 months ago
PAC Learning with Nasty Noise
We introduce a new model for learning in the presence of noise, which we call the Nasty Noise model. This model generalizes previously considered models of learning with noise. Th...
Nader H. Bshouty, Nadav Eiron, Eyal Kushilevitz