基于CUDA和Intel多核架构的脑电数据独立分量分析算法

IF 1.2 Q3 Computer Science

Bio-Algorithms and Med-Systems Pub Date : 2020-09-01 DOI:10.1515/BAMS-2020-0044

Anna Gajos-Balinska, Grzegorz M. Wójcik, Przemysław Stpiczyński

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引用次数: 0

摘要

目的脑电图信号在很大程度上暴露于外界干扰。因此，其加工的一个重要因素是它的彻底清洗。方法独立分量分析(ICA)是常用的信号改进方法之一。然而，它是一个计算量很大的算法，因此需要方法来减少它的执行时间。为了缩短算法的执行时间，采用了一种ICA算法(fastICA)，并在CPU和GPU上进行并行计算。结果本文给出了利用一些多核架构和GPU计算能力实现fastICA的研究结果。结论采用这种混合方法可以缩短算法的执行时间。

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Cooperation of CUDA and Intel multi-core architecture in the independent component analysis algorithm for EEG data

Abstract Objectives The electroencephalographic signal is largely exposed to external disturbances. Therefore, an important element of its processing is its thorough cleaning. Methods One of the common methods of signal improvement is the independent component analysis (ICA). However, it is a computationally expensive algorithm, hence methods are needed to decrease its execution time. One of the ICA algorithms (fastICA) and parallel computing on the CPU and GPU was used to reduce the algorithm execution time. Results This paper presents the results of study on the implementation of fastICA, which uses some multi-core architecture and the GPU computation capabilities. Conclusions The use of such a hybrid approach shortens the execution time of the algorithm.

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来源期刊

Bio-Algorithms and Med-Systems MATHEMATICAL & COMPUTATIONAL BIOLOGY-

CiteScore

3.80

自引率

0.00%

发文量

期刊介绍： The journal Bio-Algorithms and Med-Systems (BAMS), edited by the Jagiellonian University Medical College, provides a forum for the exchange of information in the interdisciplinary fields of computational methods applied in medicine, presenting new algorithms and databases that allows the progress in collaborations between medicine, informatics, physics, and biochemistry. Projects linking specialists representing these disciplines are welcome to be published in this Journal. Articles in BAMS are published in English. Topics Bioinformatics Systems biology Telemedicine E-Learning in Medicine Patient''s electronic record Image processing Medical databases.