In this work, various Bayesian methods for deconvolution and blind deconvolu- tion of sparse processes are studied. By using the prior assumption of sparsity, decon- volution and blind deconvolution operations are mapped ...

In this thesis, we investigate probabilistic methods for time series classification and clustering problems. For various classification and clustering tasks, we survey different time series models such as Markov models, ...