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DSMML
2004
Springer
15 years 3 months ago
Transformations of Gaussian Process Priors
Abstract. Gaussian process prior systems generally consist of noisy measurements of samples of the putatively Gaussian process of interest, where the samples serve to constrain the...
Roderick Murray-Smith, Barak A. Pearlmutter
ICDCS
2009
IEEE
15 years 6 months ago
Modeling Probabilistic Measurement Correlations for Problem Determination in Large-Scale Distributed Systems
With the growing complexity in computer systems, it has been a real challenge to detect and diagnose problems in today’s large-scale distributed systems. Usually, the correlatio...
Jing Gao, Guofei Jiang, Haifeng Chen, Jiawei Han
100
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IDA
1999
Springer
15 years 1 months ago
Reasoning about Input-Output Modeling of Dynamical Systems
The goal of input-output modeling is to apply a test input to a system, analyze the results, and learn something useful from the causeeffect pair. Any automated modeling tool that...
Matthew Easley, Elizabeth Bradley
IWANN
2009
Springer
15 years 4 months ago
Switching Dynamics of Neural Systems in the Presence of Multiplicative Colored Noise
We study the dynamics of a simple bistable system driven by multiplicative correlated noise. Such system mimics the dynamics of classical attractor neural networks with an addition...
Jorge F. Mejías, Joaquín J. Torres, ...
ARC
2010
Springer
154views Hardware» more  ARC 2010»
14 years 9 months ago
Perspectives on system identification
: System identification is the art and science of building mathematical models of dynamic systems from observed input-output data. It can be seen as the interface between the real ...
Lennart Ljung