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題名 | Fractal Analysis of Biomedical Signals= |
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作者 | Akay,Metin; Fischer,Russell; |
期刊 | 醫學工程 |
出版日期 | 19970800 |
卷期 | 9:4 1997.08[民86.08] |
頁次 | 頁23-27 |
分類號 | 410.1644 |
語文 | eng |
關鍵詞 | 碎形布朗運動; 醫學工程; Fractional brownian motion; FBM; |
英文摘要 | Fractional Brownian motion (FBM) provides a useful model for many physical phenomena with power spectral densities (PSDs) inversely proportional to frequency. In this model, only one parameter is necessary to describe the complexity of the data, H the Hurst exponent. FBM is a nonstationary random function not well suited to analysis by the discrete Fourier transform (DFT) however. In this paper we discuss two alternative methods for the analysis of FBM, one based upon maximum likelihood estimation (MLE) the other on the discrete wavelet transform (DWT), and compare the accuracy and precision of their estimates on synthesized FBM datasets. It is found that the estimates provided by the MLE method have lower variance and better accuracy in general. however the DWT method may be better suited to situations in which it is desired to monitor changes in H in real-time. The applicability of the methods to the analysis of heart rate variability is discussed |
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