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A distributed computing system for multivariate time series analyses of multichannel neurophysiological data.

Abstract：

:We present a client-server application for the distributed multivariate analysis of time series using standard PCs. We here concentrate on analyses of multichannel EEG/MEG data, but our method can easily be adapted to other time series. Due to the rapid development of new analysis techniques, the focus in the design of our application was not only on computational performance, but also on high flexibility and expandability of both the client and the server programs. For this purpose, the communication between the server and the clients as well as the building of the computational tasks has been realized via the Extensible Markup Language (XML). Running our newly developed method in an asynchronous distributed environment with random availability of remote and heterogeneous resources, we tested the system's performance for a number of different univariate and bivariate analysis techniques. Results indicate that for most of the currently available analysis techniques, calculations can be performed in real time, which, in principle, allows on-line analyses at relatively low cost.

journal_name

J Neurosci Methods

journal_title

Journal of neuroscience methods

authors

Müller A,Osterhage H,Sowa R,Andrzejak RG,Mormann F,Lehnertz K

doi

10.1016/j.jneumeth.2005.09.002

subject

Has Abstract

pub_date

2006-04-15 00:00:00

pages

190-201

issue

1-2

eissn

0165-0270

issn

1872-678X

pii

S0165-0270(05)00312-2

journal_volume

152

pub_type

杂志文章

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