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» Analysis and Application of Adaptive Sampling
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TSP
2010
13 years 4 months ago
Distributed sampling of signals linked by sparse filtering: theory and applications
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
ISNN
2010
Springer
13 years 8 months ago
MULP: A Multi-Layer Perceptron Application to Long-Term, Out-of-Sample Time Series Prediction
Abstract. A forecasting approach based on Multi-Layer Perceptron (MLP) Artificial Neural Networks (named by the authors MULP) is proposed for the NN5 111 time series long-term, out...
Eros Pasero, Giovanni Raimondo, Suela Ruffa
PRL
2010
149views more  PRL 2010»
13 years 4 months ago
Adaptive linear models for regression: Improving prediction when population has changed
The general setting of regression analysis is to identify a relationship between a response variable Y and one or several explanatory variables X by using a learning sample. In a ...
Charles Bouveyron, Julien Jacques
SIGMOD
2008
ACM
158views Database» more  SIGMOD 2008»
14 years 10 months ago
Sampling cube: a framework for statistical olap over sampling data
Sampling is a popular method of data collection when it is impossible or too costly to reach the entire population. For example, television show ratings in the United States are g...
Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, Y...
IMAGING
2001
13 years 11 months ago
Spherical Sampling and Color Transformations
In this paper, we present a spherical sampling technique that can be employed to find optimal sensors for trichromatic color applications. The advantage over other optimization te...
Graham D. Finlayson, Sabine Süsstrunk