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Unsupervised learning for signal versus noise (Corresp.)

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1 Author(s)

The Bayes solution to the unsupervised sequential learning problem induced by a mixture model for the two-class signal versus noise decision problem generates a computational and storage explosion. A quasi-Bayes approximate learning procedure is proposed that avoids the computational explosion while retaining the flavor of the Bayes solution. Convergence is established and efficiency is investigated.

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Information Theory, IEEE Transactions on  (Volume:27 ,  Issue: 4 )