DocumentCode
1938698
Title
Modeling the Dynamics of the Human Pulse Data by MDL-optimal Neural Networks
Author
Ma, Yingnan ; Zhao, Yi ; Fan, Youhua ; Hu, Hong ; Zhang, Xiujun
Author_Institution
Shenzhen Grad. Sch., Harbin Inst. of Technol., Shenzhen
Volume
2
fYear
2008
fDate
27-30 May 2008
Firstpage
460
Lastpage
463
Abstract
In this paper, we describe an information theoretic criterion, the method of minimum description length (MDL), to determine optimal neural networks to predict the human pulse data as well as non-stationary Lorenz data. Such optimal models which minimize the description length of the data both generalize well and accurately capture the dynamics of the original data. It demonstrates the potential utility of our MDL-optimal model in biomedical time series modeling.
Keywords
information theory; medical signal processing; neural nets; time series; biomedical time series; human pulse dynamics; information theoretic criterion; minimum description length; nonstationary Lorenz data; optimal neural networks; Artificial neural networks; Biomedical engineering; Biomedical informatics; Costs; Humans; Information science; Neural networks; Neurons; Predictive models; Testing; Human Pulse Data; MDL-optimal;
fLanguage
English
Publisher
ieee
Conference_Titel
BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on
Conference_Location
Sanya
Print_ISBN
978-0-7695-3118-2
Type
conf
DOI
10.1109/BMEI.2008.74
Filename
4549215
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