Time-domain fast fixed-point algorithms for convolutive ICA

Algorithmes temporels rapides de type point fixe pour la séparation aveugle de mélanges convolutifs Time-domain fast fixed-point algorithms for blind separation of convolutive mixtures

This paper presents new blind separation methods for Moving Average (MA) convolutive mixtures of independent MA processes. They consist of time-domain extensions of the FastICA algorithms developed by Hyvärinen and Oja for instantaneous mixtures. They perform a convolutive sphering in order to use parameter-free fast fixed-point algorithms associated with kurtotic or negentropic nongaussianity ...

New Fixed-point Ica Algorithms for Convolved Mixtures

One of the most powerful techniques applied to blind audio source separation is Independent Component Analysis (ICA). For the separation of audio sources recorded in a real environment, we need to model the mixing process as convolutional. Many methods have been introduced for separating convolved mixtures, the most successful of which require working in the frequency domain [1], [2], [3], [4]....

Monotonic convergence of fixed-point algorithms for ICA

We re-examine a fixed-point algorithm proposed by Hyvarinen for independent component analysis, wherein local convergence is proved subject to an ideal signal model using a square invertible mixing matrix. Here, we derive step-size bounds which ensure monotonic convergence to a local extremum for any initial condition. Our analysis does not assume an ideal signal model but appeals rather to pro...

Convolutive ICA for Audio Signals

Fast algorithms for weighted myriad computation by fixed-point search

This paper develops fast algorithms to compute the output of the weighted myriad filter. Myriad filters form a large and important class of nonlinear filters for robust non-Gaussian signal processing and communications in impulsive noise environments. Just as the weighted mean and the weighted median are optimized for the Gaussian and Laplacian distributions, respectively, the weighted myriad i...