Anna Gajos-Balinska, Grzegorz M. Wójcik, Przemysław Stpiczyński
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引用次数: 0
Abstract
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.
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.