| 肾综合征出血热变化趋势的小波分析 |
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| 引用本文： | 吴学森,王洁贞,丁守銮,由智勇,刘云霞. 肾综合征出血热变化趋势的小波分析[J]. 中国卫生统计, 2004, 21(1): 17-20 |
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| 作者姓名： | 吴学森 王洁贞 丁守銮 由智勇 刘云霞 |
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| 作者单位： | 山东大学公共卫生学院卫生统计学教研室,250012 |
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| 摘 要： | 目的探讨小波分析在肾综合征出血热(HFRS)变化趋势特征提取上的应用.方法用Meyer型小波基函数对HFRS资料作五层小波分解,然后对低频和高频成份分别进行重构,从而提取出HFRS资料的趋势特征.结果HFRS的短、中期的周期性变化较明显,以6个月和1年的时间作为它们的变化周期,而长期趋势揭示目前HFRS发病率在高位振荡.结论小波分析对具有周期性变化趋势的医学资料有很好的特征提取能力.
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| 关 键 词： | 肾综合征出血热 小波分析 多尺度分析 |
The Application of Wavelet Analysis in Haemorrhagic Fever with Renal Syndrome (HFRS) Periodical Trend |
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| Wu Xuesen,Wang Jiezhen,Ding Shouluan,et al.. The Application of Wavelet Analysis in Haemorrhagic Fever with Renal Syndrome (HFRS) Periodical Trend[J]. Chinese Journal of Health Statistics, 2004, 21(1): 17-20 |
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| Authors: | Wu Xuesen Wang Jiezhen Ding Shouluan et al. |
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| Abstract: | Objective To explor the application of wavelet analysis in Haemorrhagic Fever with Renal Syndrome(HFRS) period.Methods A five-scale wavelet transform is need for HFRS data with Meyer's wavelet function,then reconstructure the low frequency and high frequency respectively.Results HFRS has six-month short period and twelve-month middle period .The long trend shows that the change of HFRS has the state of oscillation in high.Conclusion Wavelet analysis can be used to analyse the medical data that has periodical trend change. |
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| Keywords: | Haemorrhagic Fever with Renal Syndrome Wavelet analysis Multi-resolution |
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