Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Neural systems are composed of a large number of highly-connected neurons and are widely simulated within the neurological community. In this paper, we examine the application of ...
Collin J. Lobb, Zenas Chao, Richard M. Fujimoto, S...
Studies of the fault-tolerance of graphs have tended to largely concentrate on classical graph connectivity. This measure is very basic, and conveys very little information for des...
Vijay Lakamraju, Zahava Koren, Israel Koren, C. Ma...
Hybrid systems are models for complex physical systems and are defined as dynamical systems with interacting discrete transitions and continuous evolutions along differential equa...
A probabilistic, ``neural'' approach to sensor modelling and classification is described, performing local data fusion in a wireless system for embedded sensors using a ...