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Additive asynchronous and cyclostationary impulsive noise limits communication performance in OFDM powerline communication (PLC) systems. Conventional OFDM receivers assume additive white Gaussian noi...
There is increasing interest in broad application areas in defining flexible joint models for data having a variety of measurement scales, while also allowing data of complex types, such as functions,...
We address the sparse signal recovery problem in the context of multiple measurement vectors (MMV) when elements in each nonzero row of the solution matrix are temporally correlated. Existing algorith...
We address the sparse signal recovery problem in the context of multiple measurement vectors (MMV) when elements in each nonzero row of the solution matrix are temporally correlated. Existing algorith...
We propose a simple and efficient Bayesian model of iterative learning on social networks. This model is efficient in two senses: the process both results in an optimal belief, and can be carried ou...
A key problem in statistics and machine learning is inferring suitable structure of a model given some observed data. A Bayesian approach to model comparison makes use of the marginal likelihood of ...
We provide a reason for Bayesian updating, in the Bernoulli case, even when it is assumed observations are independent and identically distributed with fixed but unknown parameter 0. The motivation...

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