A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Using Correspondence Analysis to Combine Classifiers
Machine Learning
Quickest change detection of a Markov process across a sensor array
IEEE Transactions on Information Theory
Coalition formation for bearings-only localization in sensor networks: a cooperative game approach
IEEE Transactions on Signal Processing
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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The paper deals with a mathematical model of a surveillance system based on a net of sensors. The signals acquired by each node of the net are Markovian process, have two different transition probabilities, which depends on the presence or absence of a intruder nearby. The detection of the transition probability change at one node should be confirmed by a detection of similar change at some other sensors. Based on a simple game the model of a fusion center is then constructed. The aggregate function defined on the net is the background of the definition of a non-cooperative stopping game which is a model of the multivariate disorder detection.