One of the major limitations of HMM-based models is the inability to cope with topology: When applied to a visible observation (VO) sequence, HMM-based techniques have difficulty ...
—In this paper we describe a novel approach, called improbability filtering, to rejecting false-positive observations from degrading the tracking performance of an Extended Kalma...
Brett Browning, Michael H. Bowling, Manuela M. Vel...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Abstract--A new approach to the design of wireless data broadcasting systems is introduced. The proposed approach is based on the mathematical analysis of the aforementioned system...
Christos Liaskos, Sophia G. Petridou, Georgios I. ...
The classical inexact Newton algorithm is an efficient and popular technique for solving large sparse nonlinear system of equations. When the nonlinearities in the system are wellb...