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 ...
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...
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...
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...
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...