ProcessingIndependent Component Analysis : Source Assessment & Separation , a Bayesian Approach
نویسنده
چکیده
This paper presents a method of independent component analysis which assesses the most probable number of source sequences from a larger number of observed sequences and estimates the unknown source sequences and mixing matrix. The estimation of the number of true sources is regarded as a model-order estimation problem and is tackled under a Bayesian paradigm. The method is shown to give good results on both synthetic and real data.
منابع مشابه
Advanced source separation methods with applications to spatio-temporal datasets
Latent variable models are useful tools for statistical data analysis in many applications. Examples of popular models include factor analysis, state-space models and independent component analysis. These types of models can be used for solving the source separation problem in which the latent variables should have a meaningful interpretation and represent the actual sources generating data. So...
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