Classification of Time Series Using Singular Values and Wavelet Subband Analysis with ANN and SVM Classifiers

被引：3

作者：

Benyo, Balazs ^{[1
]}

Somogyi, Peter ^{[2
]}

Palancz, Bela ^{[3
]}

机构：

[1] Szechenyi Istvan Univ, Dept Informat Technol, Egyet Ter 1, H-9026 Gyor, Hungary

[2] Budapest Univ Technol & Econ, Dept Control Engn & Informat Technol, H-1117 Budapest, Hungary

[3] Budapest Univ Technol & Econ, Dept Photogrammetry & Geoinformat, H-1117 Budapest, Hungary

来源：

JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | 2006年 / 10卷 / 04期

关键词：

biomedical classification; neural-network model; radial base function network; support vector machine;

D O I：

10.20965/jaciii.2006.p0498

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Oscillation of cerebral blood flow (CBF) in physiological or pathophysiological brain states is common, therefore it is promising to identify cerebral circulation disorders based on CBF signal classification. To characterize temporal blood flow patterns, we applied two feature extractions, spectral matrix and wavelet subband analysis. To distinguish between different physiological states, two different classifications have been developed - the radial basis function- based neural network and a support vector classifier with a Gaussian kernel. Feature extraction and classification are evaluated and their efficiency compared. Calculation was done using Mathematica 5.1 and its Wavelet Application.

引用

页码：498 / 503

页数：6

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