When large amount of statistical information about power system component failure rate is available, statistical parametric models can be developed for predictive maintenance. Oft...
Miroslav Begovic, Petar M. Djuric, Joshua Perkel, ...
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
—We propose a new parametric class of scheduling and routing policies for open multiclass queueing networks. We establish their stability and show they are amenable to distribute...
Ioannis Ch. Paschalidis, Chang Su, Michael Caraman...
This paper presents a new method for the selection of the two hyperparameters of Least Squares Support Vector Machine (LS-SVM) approximators with Gaussian Kernels. The two hyperpar...
Amaury Lendasse, Yongnan Ji, Nima Reyhani, Michel ...
— In this paper we present an approach for localizing a sensor network augmented with a mobile robot which is capable of providing inter-sensor pose estimates through its odometr...
David Meger, Dimitri Marinakis, Ioannis M. Rekleit...