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AMFG
2003
IEEE
113views Biometrics» more  AMFG 2003»
15 years 11 months ago
Sequential Monte Carlo Tracking of Body Parameters in a Sub-Space
In recent years Sequential Monte Carlo (SMC) methods have been applied to handle some of the problems inherent to model-based tracking. In this paper two issues regarding SMC are ...
Thomas B. Moeslund, Erik Granum
ICANN
2001
Springer
15 years 11 months ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc
ISSS
1999
IEEE
157views Hardware» more  ISSS 1999»
15 years 10 months ago
Bit-Width Selection for Data-Path Implementations
Specifications of data computations may not necessarily describe the ranges of the intermediate results that can be generated. However, such information is critical to determine t...
Carlos Carreras, Juan A. López, Octavio Nie...
AUTOMATICA
2005
103views more  AUTOMATICA 2005»
15 years 6 months ago
Periodic signal analysis by maximum likelihood modeling of orbits of nonlinear ODEs
This paper treats a new approach to the problem of periodic signal estimation. The idea is to model the periodic signal as a function of the state of a second-order nonlinear ordi...
Torsten Söderström, Torbjörn Wigren...
TMI
2008
138views more  TMI 2008»
15 years 5 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...