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» Gaussian process for nonstationary time series prediction
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IDEAL
2005
Springer
14 years 2 months ago
Neural Networks: A Replacement for Gaussian Processes?
Abstract. Gaussian processes have been favourably compared to backpropagation neural networks as a tool for regression. We show that a recurrent neural network can implement exact ...
Matthew Lilley, Marcus R. Frean
ICONIP
2008
13 years 10 months ago
An Exemplar-Based Statistical Model for the Dynamics of Neural Synchrony
Abstract. A method is proposed to determine the similarity of a collection of time series. As a first step, one extracts events from the time series, in other words, one converts e...
Justin Dauwels, François B. Vialatte, Theop...
ASPDAC
2008
ACM
200views Hardware» more  ASPDAC 2008»
13 years 10 months ago
Non-Gaussian statistical timing analysis using second-order polynomial fitting
In the nanometer manufacturing region, process variation causes significant uncertainty for circuit performance verification. Statistical static timing analysis (SSTA) is thus dev...
Lerong Cheng, Jinjun Xiong, Lei He
VLDB
2007
ACM
179views Database» more  VLDB 2007»
14 years 8 months ago
Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data
Market analysis is a representative data analysis process with many applications. In such an analysis, critical numerical measures, such as profit and sales, fluctuate over time a...
Xiaolei Li, Jiawei Han
ICASSP
2008
IEEE
14 years 3 months ago
On the synchrony of empirical mode decompositions with application to electroencephalography
A novel approach to measure the interdependence of time series is proposed, based on the alignment (“matching”) of their Huang-Hilbert spectra. The method consists of three st...
Justin Dauwels, Tomasz M. Rutkowski, Franço...