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Efficient Implementing of DNA Computing-inspired Pattern Classifier Using GPU  

Choi, Sun-Wook (인하대 공대 정보통신공학과)
Lee, Chong-Ho (인하대 공대 정보통신공학과)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.58, no.7, 2009 , pp. 1424-1434 More about this Journal
Abstract
DNA computing-inspired pattern classification based on the hypernetwork model is a novel approach to pattern classification problems. The hypernetwork model has been shown to be a powerful tool for multi-class data analysis. However, the ordinary hypernetwork model has limitations, such as operating sequentially only. In this paper, we propose a efficient implementing method of DNA computing-inspired pattern classifier using GPU. We show simulation results of multi-class pattern classification from hand-written digit data, DNA microarray data and 8 category scene data for performance evaluation. and we also compare of operation time of the proposed DNA computing-inspired pattern classifier on each operating environments such as CPU and GPU. Experiment results show competitive diagnosis results over other conventional machine learning algorithms. We could confirm the proposed DNA computing-inspired pattern classifier, designed on GPU using CUDA platform, which is suitable for multi-class data classification. And its operating speed is fast enough to comply point-of-care diagnostic purpose and real-time scene categorization and hand-written digit data classification.
Keywords
DNA Computing; Hypernetwork; Pattern Classification; GPU;
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Times Cited By KSCI : 3  (Citation Analysis)
Times Cited By SCOPUS : 0
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