Elements of information theory
Elements of information theory
L1 solution of overdetermined systems of linear equations
ACM Transactions on Mathematical Software (TOMS)
From error probability to information theoretic (multi-modal) signal processing
Signal Processing - Special issue: Information theoretic signal processing
Hypothesis testing over factorizations for data association
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Speaker association with signal-level audiovisual fusion
IEEE Transactions on Multimedia
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Relating information originating from disparate sensors observing a given scene is a challenging task, particularly when an appropriate model of the environment or the behaviour of any particular object within it is not available. One possible strategy to address this task is to examine whether the sensor outputs contain information which can be attributed to a common cause. In this paper, we present an approach to localise this embedded common information through an indirect method of estimating mutual information between all signal sources. Ability of L1 regularization to enforce sparseness of the solution is exploited to identify a subset of signals that are related to each other, from among a large number of sensor outputs. As opposed to the conventional L2 regularization, the proposed method leads to faster convergence with much reduced spurious associations. Simulation and experimental results are presented to validate the findings.