… Bayesian Regularized Neural Network (BRNN) BRNN is combination of Bayesian inference
and Artificial Neural network (… networks and minimizes the lengthy cross validation [61], [62]. …

… A prerequisite for use of a sensor network is knowledge of the sensor, or node, positions.
In a randomly deployed ad hoc network this … A performance analysis is given in Section 5. …

… By using Bayesian inference, the value of certain network parameters can be predicted … the
Bayesian inference, the access point will declare the appropriate configuration to the network …

… These devices are generally connected to the organization's wireless network; … In this work,
we employ Bayesian inference model to compute the trust values … Bayesian inference model …

… MAC layer anomalies using cross-feature analysis on feature vectors constructed from the
… In section 3 we present a dynamic Bayesian game model for cooperative sensor networks. …

… We propose a Bayesian approach for reputation representation… We propose to use a Bayesian
approach for the representation … an estimation of θ by inference from the data obtained by …

… communicating spontaneously over the air (wireless).The topology of the network is changing
frequently because of the mobile nature of its nodes. Ad hoc finally induces that there are …

… The optimal number of states, in addition to all of the various HMM model parameters in (3)-(6),
are learned from the observable data by Bayesian posterior inference using a Gibbs …

… ad hoc networks on highways”, EURASIP Journal on Wireless Communications and
Networking … in vehicular ad hoc networks”, EURASIP Journal on Wireless Communications and …

… wireless multi–hop networks. In this paper, we analyze a scenario where two wireless ad hoc
networks … Bayesian network analysis is exploited to compute the probabilistic relationships …