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...
Neural networks are a useful alternative to Gaussian mixture models for acoustic modeling; however, training multilayer networks involves a difficult, nonconvex optimization that...
As wireless networks have become more complex with packet services and sophisticated modulation techniques, validation using multidimensional Markov Chain models has become increa...
In this paper, we propose the localized adaptive QoS routing scheme using POMDP(partially observable Markov Decision Processes) and Exploration Bonus. In order to deal with POMDP p...
This paper describes a technique for the probabilistic self-localization of a sensor network based on noisy inter-sensor range data. Our method is based on a number of parallel in...