Bayesian MLP neural networks are a flexible tool in complex nonlinear problems. The approach is complicated by need to evaluate integrals over high-dimensional probability distri...
Routing in computer networks is a nonlinear combinatorial optimization problem with numerous constraints and is classified as an NP-complete problem. There are certain important Qo...
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
: A genetic algorithm (GA) based recurrent fuzzy neural network modeling method for dynamic nonlinear chemical process is presented. The dynamic recurrent fuzzy neural network (RFN...
Abstract— This paper is concerned with control applications over lossy data networks. Sensor data is transmitted to an estimation-control unit over a network, and control command...
Emanuele Garone, Bruno Sinopoli, Alessandro Casavo...