The FastICA algorithm is one of the most prominent methods to solve the problem of linear independent component analysis (ICA). Although there have been several attempts to prove local convergence ...

Kujiraoka concludes: "We’ve used the same baseline to balance The Rising Tide, so I hope players enjoy the combat in this chapter of DLC as well!" So there you have it, The Rising Tide is ...

Blind source separation (BSS) is a problem that appears in many research fields. Fast Independent components analysis (FastICA) is one of the techniques to solve the problem. The researchers have ...

In this study, a combination model of FastICA and sparsity prior with respect to fMRI signal analysis, named SFICA, is presented. In this model, the sparse decomposition is performed on the fMRI ...

For 3 of the runs across subjects, I get: /usr/lib/python2.7/dist-packages/sklearn/decomposition/fastica_.py:116: UserWarning: FastICA did not converge. Consider increasing tolerance or the maximum ...

FastICA currently looks for n_components between 10 and 2000, with a default of 100. However, assuming there are more rows N than columns M, a data set can only support up to M independent components.