We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...
In this paper, Receding Horizon Model Predictive Control (RHMPC) of nonlinear systems subject to input and state constraints is considered. We propose to estimate the terminal reg...
for data abstraction and justifies reasoning by simulation. Representation independence has been shown for a variety of languages and constructs but not for shared references to mu...
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
In this paper we present a technique for prediction of electrical demand based on multiple models. The multiple models are composed by several local models, each one describing a r...
J. Jesus Rico Melgoza, Juan J. Flores, Constantino...