围绕现有时间段编码存在的问题与现状,提出了一种时间段剖分编码方法:多尺度时间段的整数编码(multi-scale time segment integer coding,MTSIC)。该方法通过整数间形成的树状结构和大小排序,体现了不同尺度时间段间的先后、包含/被包...围绕现有时间段编码存在的问题与现状,提出了一种时间段剖分编码方法:多尺度时间段的整数编码(multi-scale time segment integer coding,MTSIC)。该方法通过整数间形成的树状结构和大小排序,体现了不同尺度时间段间的先后、包含/被包含、相交等时间关系,最终实现了对多种尺度时间的统一整数编码化处理。在此基础上,还研究了MTSIC的时间关系的计算方法,用以支持基于时间段剖分的高效计算与查询,并初步探讨了MTSIC的应用方法与前景。试验表明,MTSIC的实现方便可靠,与传统方法转换便捷。展开更多
针对多尺度时间序列各尺度发展趋势及整体预测问题,建立小波分解回声状态网络预测模型(wavelet decomposi-tion and echo state networks,WDESN),根据各尺度的不同性质选取与之相匹配的回声状态网络模型(echo state networks,ESN),同时...针对多尺度时间序列各尺度发展趋势及整体预测问题,建立小波分解回声状态网络预测模型(wavelet decomposi-tion and echo state networks,WDESN),根据各尺度的不同性质选取与之相匹配的回声状态网络模型(echo state networks,ESN),同时,通过在各尺度条件下引入权值系数实现预测分量最优整合,提高整体预测精度。预测带噪多尺度正弦序列实验表明:WDESN模型与ESN、支持向量机及BP神经网络模型相比预测精度较高。目前,该模型已成功用于移动通信话务量的预测,并满足了现实系统的精度要求。展开更多
Based on monthly river runoff and meteorological data, a method of Morlet wavelet transform was used to analyze the multiple time scale characteristics of river runoff in the Dagujia River Basin, Yantai City, Shandong...Based on monthly river runoff and meteorological data, a method of Morlet wavelet transform was used to analyze the multiple time scale characteristics of river runoff in the Dagujia River Basin, Yantai City, Shandong Province. The results showed that the total annual river runoffin the Dagujia River Basin decreased significantly from 1966 to 2004, and the rate of decrease was 48× 10^6ma/10yr, which was higher than the mean value of most rivers in China. Multiple time scale characteristics existed, which accounted for different aspects of the changes in annual river runoff, and the major periods of the runofftime series were identified as about 28 years, 14 years and 4 years with decreasing levels of fluctuation. The river runoff evolution process was controlled by changes in precipitation to a certain extent, but it was also greatly influenced by human activities. Also, for different time periods and scales, the impacts of climate changes and human activities on annual river runoff evolution occurred at the same time. Changes in the annual river runoffwere mainly associated with climate change before the 1980s and with human activities after 1981.展开更多
Clinical disorders often are characterized by a breakdown in dynamical processes that contribute to the control of upright standing.Disruption to a large number of physiological processes operating at different time s...Clinical disorders often are characterized by a breakdown in dynamical processes that contribute to the control of upright standing.Disruption to a large number of physiological processes operating at different time scales can lead to alterations in postural center of pressure(Co P)fluctuations.Multiscale entropy(MSE) has been used to identify differences in fluctuations of postural Co P time series between groups with and without known physiological impairments at multiple time scales.The purpose of this paper is to:1) review basic elements and current developments in entropy techniques used to assess physiological complexity;and 2) identify how MSE can provide insights into the complexity of physiological systems operating at multiple time scales that underlie the control of posture.We review and synthesize evidence from the literature providing support for MSE as a valuable tool to evaluate the breakdown in the physiological processes that accompany changes due to aging and disease in postural control.This evidence emerges from observed lower MSE values in individuals with multiple sclerosis,idiopathic scoliosis,and in older individuals with sensory impairments.Finally,we suggest some future applications of MSE that will allow for further insight into how physiological deficits impact the complexity of postural fluctuations;this information may improve the development and evaluation of new therapeutic interventions.展开更多
文摘围绕现有时间段编码存在的问题与现状,提出了一种时间段剖分编码方法:多尺度时间段的整数编码(multi-scale time segment integer coding,MTSIC)。该方法通过整数间形成的树状结构和大小排序,体现了不同尺度时间段间的先后、包含/被包含、相交等时间关系,最终实现了对多种尺度时间的统一整数编码化处理。在此基础上,还研究了MTSIC的时间关系的计算方法,用以支持基于时间段剖分的高效计算与查询,并初步探讨了MTSIC的应用方法与前景。试验表明,MTSIC的实现方便可靠,与传统方法转换便捷。
文摘针对多尺度时间序列各尺度发展趋势及整体预测问题,建立小波分解回声状态网络预测模型(wavelet decomposi-tion and echo state networks,WDESN),根据各尺度的不同性质选取与之相匹配的回声状态网络模型(echo state networks,ESN),同时,通过在各尺度条件下引入权值系数实现预测分量最优整合,提高整体预测精度。预测带噪多尺度正弦序列实验表明:WDESN模型与ESN、支持向量机及BP神经网络模型相比预测精度较高。目前,该模型已成功用于移动通信话务量的预测,并满足了现实系统的精度要求。
基金The Scientific Research Foundation of Suzhou University of Science and Technology (No.332311106)the National Natural Science Foundation of China (No.52078087)111 Project of the Ministry of Education and the Bureau of Foreign Experts of China (No.B18062)。
基金Under the auspices of National Key Science and Technology Support Program of China (No. 2006BCA01A07-2)National Natural Science Foundation of China (No. 40101005)Science Foundation of Shandong Province, China (No. Q02E03)
文摘Based on monthly river runoff and meteorological data, a method of Morlet wavelet transform was used to analyze the multiple time scale characteristics of river runoff in the Dagujia River Basin, Yantai City, Shandong Province. The results showed that the total annual river runoffin the Dagujia River Basin decreased significantly from 1966 to 2004, and the rate of decrease was 48× 10^6ma/10yr, which was higher than the mean value of most rivers in China. Multiple time scale characteristics existed, which accounted for different aspects of the changes in annual river runoff, and the major periods of the runofftime series were identified as about 28 years, 14 years and 4 years with decreasing levels of fluctuation. The river runoff evolution process was controlled by changes in precipitation to a certain extent, but it was also greatly influenced by human activities. Also, for different time periods and scales, the impacts of climate changes and human activities on annual river runoff evolution occurred at the same time. Changes in the annual river runoffwere mainly associated with climate change before the 1980s and with human activities after 1981.
文摘Clinical disorders often are characterized by a breakdown in dynamical processes that contribute to the control of upright standing.Disruption to a large number of physiological processes operating at different time scales can lead to alterations in postural center of pressure(Co P)fluctuations.Multiscale entropy(MSE) has been used to identify differences in fluctuations of postural Co P time series between groups with and without known physiological impairments at multiple time scales.The purpose of this paper is to:1) review basic elements and current developments in entropy techniques used to assess physiological complexity;and 2) identify how MSE can provide insights into the complexity of physiological systems operating at multiple time scales that underlie the control of posture.We review and synthesize evidence from the literature providing support for MSE as a valuable tool to evaluate the breakdown in the physiological processes that accompany changes due to aging and disease in postural control.This evidence emerges from observed lower MSE values in individuals with multiple sclerosis,idiopathic scoliosis,and in older individuals with sensory impairments.Finally,we suggest some future applications of MSE that will allow for further insight into how physiological deficits impact the complexity of postural fluctuations;this information may improve the development and evaluation of new therapeutic interventions.
