Consistency of the blind source separation computed with five common algorithms for magnetoencephalogram background activity.

Comparison of Blind Source Separation Preprocessings Applied to Magnetoencephalogram Recordings to Improve the Classification of Alzheimer’s Disease Patients

This study compares diverse Blind Source Separation (BSS) techniques applied to magnetoencephalogram (MEG) background activity in order to improve the classification of Alzheimer’s Disease (AD) patients. MEG recordings from 18 AD patients and 13 control subjects were decomposed with the following BSS algorithms: AMUSE, SOBI, FastICA, and extended Infomax. Whereas AMUSE ranked the extracted BSS ...

Research of Blind Signals Separation with Genetic Algorithm and Particle Swarm Optimization Based on Mutual Information

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

Research of Blind Signals Separation with Genetic Algorithm and Particle Swarm Optimization Based on Mutual Information

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

Explorer Blind source separation to enhance spectral and non - linear features of magnetoencephalogram recordings

Regional coherence evaluation in mild cognitive impairment and Alzheimer's disease based on adaptively extracted magnetoencephalogram rhythms.

This study assesses the connectivity alterations caused by Alzheimer's disease (AD) and mild cognitive impairment (MCI) in magnetoencephalogram (MEG) background activity. Moreover, a novel methodology to adaptively extract brain rhythms from the MEG is introduced. This methodology relies on the ability of empirical mode decomposition to isolate local signal oscillations and constrained blind so...