Separation and Localisation of P300 Sources and Their Subcomponents Using Constrained Blind Source Separation
نویسندگان
چکیده
Separation and localisation of P300 sources and their constituent subcomponents for both visual and audio stimulations is investigated in this paper. An effective constrained blind source separation (CBSS) algorithm is developed for this purpose. The algorithm is an extension of the Infomax BSS system for which a measure of distance between a carefully measured P300 and the estimated sources is used as a constraint. During separation, the proposed CBSS method attempts to extract the corresponding P300 signals. The locations of the corresponding sources are then estimated with some indeterminancy in the results. It can be seen that the locations of the sources change for a schizophrenic patient. The experimental results verify the statistical significance of the method and its potential application in the diagnosis and monitoring of schizophrenia.
منابع مشابه
Localization of P300 Sources in Schizophrenia Patients Using Constrained BSS
A robust constrained blind source separation (CBSS) algorithm has been proposed for separation and localization of the P300 sources in schizophrenia patients. The algorithm is an extension of the Infomax algorithm, based on minimization of mutual information, for which a reference P300 signal is used as a constraint. The reference signal forces the unmixing matrix to separate the sources of bot...
متن کاملResearch 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...
متن کاملResearch 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...
متن کاملTensor based source separation for single and multichannel signals
Blind source separation (BSS) techniques have the aim of separating original source signals from their mixtures without having or with a little knowledge about the source signals or the mixing process. Tensor based source separation techniques have become increasingly popular for various applications since they exploit different inherent diversities of the sources. Therefore, they can improve t...
متن کاملBlind Separation of Jointly Stationary Correlated Sources
The separation of unobserved sources from mixed observed data is a fundamental signal processing problem. Most of the proposed techniques for solving this problem rely on independence or at least uncorrelation assumption for source signals. This paper introduces a technique for cases that source signals are correlated with each other. The method uses Wold decomposition principle for extracting ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- EURASIP J. Adv. Sig. Proc.
دوره 2007 شماره
صفحات -
تاریخ انتشار 2007