thIs a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
thIs sample demonstrates the handling of DIF_ calls during device installation and the insertion of a property page into the install wizard and into the device properties.
thIs software was done in part for a textbook on AI I ve written called _The Basis of AI_ (tentative title, subject to change but not if I get my way). For details see: http://www.mcs.com/~drt/basisofai.html
手機文件瀏覽器 Here are the sources to SMan v1.2c 1.2 is a major jump from v1.1. You will see thIs from the way the code has been restructured into multiple files. It also supports flip closed. However, to my chagrin, I made the mistake of assuming there will only be one flip closed view. :( That s changed in v1.3 :) 1.3 supports multiple flip closed views that can be easily added into SMan.
