Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
The focus of this paper is the problem of recursive estimation for uncertain multisensor linear discrete-time systems. We herein propose a new suboptimal filtering algorithm. The b...
For component-based systems, classical techniques for Worst-Case Execution Time (WCET) estimation produce unacceptable overestimations of a components WCET. This is because softwa...
Johan Fredriksson, Thomas Nolte, Andreas Ermedahl,...
In this paper, a global methodology for the long-term prediction of time series is proposed. This methodology combines direct prediction strategy and sophisticated input selection...
Antti Sorjamaa, Jin Hao, Nima Reyhani, Yongnan Ji,...
We derive solutions for the problem of missing and noisy data in nonlinear timeseries prediction from a probabilistic point of view. We discuss different approximations to the so...