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IPSN
2005
Springer
14 years 1 months ago
The sensor selection problem for bounded uncertainty sensing models
We address the problem of selecting sensors so as to minimize the error in estimating the position of a target. We consider a generic sensor model where the measurements can be in...
Volkan Isler, Ruzena Bajcsy
NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 7 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
IJCNN
2006
IEEE
14 years 1 months ago
Modular Multilayer Perceptron for WLAN Based Localization
Location Awareness is key capability of Context-Aware Ubiquitous environments. Received Signal Strength (RSS) based localization is increasingly popular choice especially for in-bu...
Uzair Ahmad, Andrey Gavrilov, Sungyoung Lee, Young...
NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 11 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
GLOBECOM
2008
IEEE
13 years 7 months ago
Binary Consensus over Fading Channels: A Best Affine Estimation Approach
In this paper we consider a cooperative network that is trying to reach binary consensus over fading channels. We first characterize the impact of fading on network consensus by up...
Mehrzad Malmirchegini, Yongxiang Ruan, Yasamin Mos...