This prior can be incorporated in the general equation for the posterior probability and one can derive the stochastic gradient update rule where with , and . Blue The spheres are centered on the mean expected source positions and their radii denote the standard deviations. Original Waveforms are emitted by the Sources Mixed Waveforms are recorded by the Detectors Signals propagate according to an inverse-square law. BSL refers to the Bayesian method also using a super-Gaussian source amplitude density prior. The Bayesian method, using additional information about the signal propagation, can better separate the signals although separation is still not perfect due to the inappropriate source density assumptions.
More information helps, but inaccurate prior information produces inaccurate results.
Natural gradient works efficiently in learning. Neural Comp . Bell, A.J. and Sejnowski, T.J. 1995. An information-maximization approach to blind separation and blind deconvolution. Cox, R.T. 1946.