密度峰值聚类算法(density peaks clustering algorithm,DPC)是2014年提出的一种新型聚类分析算法,它基于聚类中心局部密度大以及与密度更大点之间的距离较远两大特点绘制决策图寻找聚类中心,从而得到任意形状的簇.但在寻找聚类中心的...密度峰值聚类算法(density peaks clustering algorithm,DPC)是2014年提出的一种新型聚类分析算法,它基于聚类中心局部密度大以及与密度更大点之间的距离较远两大特点绘制决策图寻找聚类中心,从而得到任意形状的簇.但在寻找聚类中心的过程中,求解局部密度以及高密度距离属性都依赖于相似度矩阵的计算,计算复杂度较高,限制了密度峰值聚类算法在大规模数据集中的应用.针对此不足,提出基于网格筛选的密度峰值聚类算法(density peaks clustering algorithm based on grid screening,SDPC),根据数据的不均匀分布,使用网格化方法去除部分密度稀疏的点,然后再使用密度峰值聚类算法中决策图的方法选取聚类中心,可以在保证聚类准确性的基础上有效降低计算复杂度.理论分析和实验测试表明:基于网格筛选的密度峰值聚类算法不仅可以对大规模数据集进行正确的聚类,还极大地降低了计算复杂度.展开更多
Existing methods of physiological signal analysis based on nonlinear dynamic theories only examine the complexity difference of the signals under a single sampling frequency.We developed a technique to measure the mul...Existing methods of physiological signal analysis based on nonlinear dynamic theories only examine the complexity difference of the signals under a single sampling frequency.We developed a technique to measure the multifractal characteristic parameter intimately associated with physiological activities through a frequency scale factor.This parameter is highly sensitive to physiological and pathological status.Mice received various drugs to imitate different physiological and pathological conditions,and the distributions of mass exponent spectrum curvature with scale factors from the electrocardiogram (ECG) signals of healthy and drug injected mice were determined.Next,we determined the characteristic frequency scope in which the signal was of the highest complexity and most sensitive to impaired cardiac function,and examined the relationships between heart rate,heartbeat dynamic complexity,and sensitive frequency scope of the ECG signal.We found that all animals exhibited a scale factor range in which the absolute magnitudes of ECG mass exponent spectrum curvature achieve the maximum,and this range (or frequency scope) is not changed with calculated data points or maximal coarse-grained scale factor.Further,the heart rate of mice was not necessarily associated with the nonlinear complexity of cardiac dynamics,but closely related to the most sensitive ECG frequency scope determined by characterization of this complex dynamic features for certain heartbeat conditions.Finally,we found that the health status of the hearts of mice was directly related to the heartbeat dynamic complexity,both of which were positively correlated within the scale factor around the extremum region of the multifractal parameter.With increasing heart rate,the sensitive frequency scope increased to a relatively high location.In conclusion,these data provide important theoretical and practical data for the early diagnosis of cardiac disorders.展开更多
文摘密度峰值聚类算法(density peaks clustering algorithm,DPC)是2014年提出的一种新型聚类分析算法,它基于聚类中心局部密度大以及与密度更大点之间的距离较远两大特点绘制决策图寻找聚类中心,从而得到任意形状的簇.但在寻找聚类中心的过程中,求解局部密度以及高密度距离属性都依赖于相似度矩阵的计算,计算复杂度较高,限制了密度峰值聚类算法在大规模数据集中的应用.针对此不足,提出基于网格筛选的密度峰值聚类算法(density peaks clustering algorithm based on grid screening,SDPC),根据数据的不均匀分布,使用网格化方法去除部分密度稀疏的点,然后再使用密度峰值聚类算法中决策图的方法选取聚类中心,可以在保证聚类准确性的基础上有效降低计算复杂度.理论分析和实验测试表明:基于网格筛选的密度峰值聚类算法不仅可以对大规模数据集进行正确的聚类,还极大地降低了计算复杂度.
基金supported by the National Natural Science Foundation of China (Grant No. 61003169)the Ph.D. Programs Foundation of Ministry of Education of China (Grant No. 20090095120013)the Technology Funding Project of China University of Mining and Technology (Grant No. 2008C004)
文摘Existing methods of physiological signal analysis based on nonlinear dynamic theories only examine the complexity difference of the signals under a single sampling frequency.We developed a technique to measure the multifractal characteristic parameter intimately associated with physiological activities through a frequency scale factor.This parameter is highly sensitive to physiological and pathological status.Mice received various drugs to imitate different physiological and pathological conditions,and the distributions of mass exponent spectrum curvature with scale factors from the electrocardiogram (ECG) signals of healthy and drug injected mice were determined.Next,we determined the characteristic frequency scope in which the signal was of the highest complexity and most sensitive to impaired cardiac function,and examined the relationships between heart rate,heartbeat dynamic complexity,and sensitive frequency scope of the ECG signal.We found that all animals exhibited a scale factor range in which the absolute magnitudes of ECG mass exponent spectrum curvature achieve the maximum,and this range (or frequency scope) is not changed with calculated data points or maximal coarse-grained scale factor.Further,the heart rate of mice was not necessarily associated with the nonlinear complexity of cardiac dynamics,but closely related to the most sensitive ECG frequency scope determined by characterization of this complex dynamic features for certain heartbeat conditions.Finally,we found that the health status of the hearts of mice was directly related to the heartbeat dynamic complexity,both of which were positively correlated within the scale factor around the extremum region of the multifractal parameter.With increasing heart rate,the sensitive frequency scope increased to a relatively high location.In conclusion,these data provide important theoretical and practical data for the early diagnosis of cardiac disorders.
