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IWANN
2005
Springer
13 years 11 months ago
Direct and Recursive Prediction of Time Series Using Mutual Information Selection
Abstract. This paper presents a comparison between direct and recursive prediction strategies. In order to perform the input selection, an approach based on mutual information is u...
Yongnan Ji, Jin Hao, Nima Reyhani, Amaury Lendasse
IJON
2002
103views more  IJON 2002»
13 years 5 months ago
RBF networks training using a dual extended Kalman filter
: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...
Iulian B. Ciocoiu
ICASSP
2009
IEEE
14 years 29 days ago
A mixed time-scale algorithm for distributed parameter estimation : Nonlinear observation models and imperfect communication
Abstract— The paper considers the algorithm NLU for distributed (vector) parameter estimation in sensor networks, where, the local observation models are nonlinear, and inter-sen...
Soummya Kar, José M. F. Moura
INFOCOM
2005
IEEE
13 years 11 months ago
Predicting Internet end-to-end delay: a multiple-model approach
This paper presents a novel approach to predict the Internet end-to-end delay using multiple-model (MM) methods. The basic idea of the MM method is to assume the system dynamics c...
Ming Yang, Jifeng Ru, X. Rong Li, Huimin Chen, Anw...
VR
2003
IEEE
267views Virtual Reality» more  VR 2003»
13 years 11 months ago
An Experiment Comparing Double Exponential Smoothing and Kalman Filter-Based Predictive Tracking Algorithms
We present an experiment comparing double exponential smoothing and Kalman filter-based predictive tracking algorithms with derivative free measurement models. Our results show t...
Joseph J. LaViola Jr.