Range-based ICA using a nonsmooth quasi-Newton optimizer for electroencephalographic source localization in focal epilepsy
Independent component analysis (ICA) aims at separating a multivariate signal into
independent nongaussian signals by optimizing a contrast function with no knowledge on …
independent nongaussian signals by optimizing a contrast function with no knowledge on …
Spherical mesh adaptive direct search for separating quasi-uncorrelated sources by range-based independent component analysis
SE Selvan, PB Borckmans, A Chattopadhyay… - Neural …, 2013 - ieeexplore.ieee.org
It is seemingly paradoxical to the classical definition of the independent component analysis
(ICA), that in reality, the true sources are often not strictly uncorrelated. With this in mind, this …
(ICA), that in reality, the true sources are often not strictly uncorrelated. With this in mind, this …
A derivative-free Riemannian Powell's method, minimizing Hartley-entropy-based ICA contrast
A Chattopadhyay, SE Selvan… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Even though the Hartley-entropy-based contrast function guarantees an unmixing local
minimum, the reported nonsmooth optimization techniques that minimize this …
minimum, the reported nonsmooth optimization techniques that minimize this …
Nonsmooth ICA contrast minimization using a Riemannian Nelder–Mead method
SE Selvan - IEEE Transactions on Neural Networks and …, 2014 - ieeexplore.ieee.org
This brief concerns the design and application of a Riemannian Nelder-Mead algorithm to
minimize a Hartley-entropy-based contrast function to reliably estimate the sources from …
minimize a Hartley-entropy-based contrast function to reliably estimate the sources from …