实验动物兔子心电图奇异性检测:进化谱方法

基于小波变换的进化谱分析能够揭示非平稳信号特定时刻的时一频域特性.实验动物兔子左冠状动脉前降支结扎实验,可以模拟早期心肌缺血症状的不同生理变化过程.左冠状动脉病变引发心肌缺血是急性心肌梗死等冠心病的早期主要征兆.文中提出了基于连续复小波变换的进化谱估计算法,在满足时一频域不确定性原理条件下,为获得非平稳信号的瞬时频谱提供了一种有效的新方法,它能够识别生命系统数据中的局部奇异性.应用这种算法对实验动物兔子的多种心电图数据的进化谱分析结果表明,QRS波群进化谱特性的变化与早期心肌缺血有内在关联.QRs波群进化谱品质因数Q是心电图在时一频域的一个特征参数,Q数值变异可能为识别早期心肌缺血提供一种新的医学诊断参考特征.     

实验动物兔子心电图奇异性检测：进化谱方法

基于小波变换的进化谱分析能够揭示非平稳信号特定时刻的时一频域特性．实验动物兔子左冠状动脉前降支结扎实验,可以模拟早期心肌缺血症状的不同生理变化过程．左冠状动脉病变引发心肌缺血是急性心肌梗死等冠心病的早期主要征兆．文中提出了基于连续复小波变换的进化谱估计算法,在满足时一频域不确定性原理条件下,为获得非平稳信号的瞬时频谱提供了一种有效的新方法,它能够识别生命系统数据中的局部奇异性．应用这种算法对实验动物兔子的多种心电图数据的进化谱分析结果表明,QRS波群进化谱特性的变化与早期心肌缺血有内在关联．QRS波群进化谱品质因数Q是心电图在时频域的一个特征参数,Q数值变异可能为识别早期心肌缺血提供一种新的医学诊断参考特征．     

Characteristic parameters from a human of electromagnetic signals heart system

The electromagnetic field of a human heart system is a bioelectromagnetic field. Electrocardiography （ECG） and magnetocardiography （MCG） are both carriers of electromagnetic information about the cardiac system, and they are nonstationary signals. In this study, ECG and MCG data from healthy subjects are acquired; the MCG data are captured using a high-Tc radio frequency superconducting quantum interference device （HTc rf SQUIDs） and the QRS complexes in these data are analysed by the evolutionary spectrum analysis method. The results show that the quality factor Q and the central frequency fz of the QRS complex evolutionary spectrum are the characteristic parameters （CHPs） of ECG and MCG in the time-frequency domain. The confidence intervals of the mean values of the CHPs are estimated by the Student t distribution method in mathematical statistics. We believe that there are threshold ranges of the mean values of Q and fz for healthy subjects. We have postulated the following criterion： if the mean values of CHPs are in the proper ranges, the cardiac system is in a normal condition and it possesses the capability of homeostasis. In contrast, if the mean values of the CHPs do not lie in the proper ranges, the homeostasis of the cardiac system is lacking and some cardiac disease may follow. The results and procedure of MCG CHPs in the study afford a technological route for the application of HTc rf SQUIDs in cardiology.     

电子信息类专业课程体系结构的一种框架

电子信息类学科属于技术科学．该学科在20世纪经历了4次技术重点的重大转移,这些转移对该学科的教学内容和人才培养方式都产生了显著影响．21世纪,电子信息类专业人才的培养在基础知识、基本技能和基本素质诸方面都将有重大变化．在总结国内外相近专业教育教学经验的基础上,提出了一种将本科生和硕士生专业教育相互衔接的“大本科”教育理念,建议了一种新的课程体系结构框架．由通用自然科学基础、技术基础和专业技术课程构成了专业课堂教学类课程体系;由基础实验、技术基础实验和专题性实验构成了实验类教学体系．专业技术类课程和专题性实验课程是本科生和硕士生相衔接的教学平台．     

Characteristic parameters of electromagnetic signals from a human heart system

The electromagnetic field of a human heart system is a bioelectromagnetic field. Electrocardiography (ECG) and magnetocardiography (MCG) are both carriers of electromagnetic information about the cardiac system,and they are nonstationary signals. In this study,ECG and MCG data from healthy subjects are acquired; the MCG data are captured using a high-T c radio frequency superconducting quantum interference device (HTc rf SQUIDs) and the QRS complexes in these data are analysed by the evolutionary spectrum analysis method. The results show that the quality factor Q and the central frequency f z of the QRS complex evolutionary spectrum are the characteristic parameters (CHPs) of ECG and MCG in the time-frequency domain. The confidence intervals of the mean values of the CHPs are estimated by the Student t distribution method in mathematical statistics. We believe that there are threshold ranges of the mean values of Q and f z for healthy subjects. We have postulated the following criterion: if the mean values of CHPs are in the proper ranges,the cardiac system is in a normal condition and it possesses the capability of homeostasis. In contrast,if the mean values of the CHPs do not lie in the proper ranges,the homeostasis of the cardiac system is lacking and some cardiac disease may follow. The results and procedure of MCG CHPs in the study afford a technological route for the application of HTc rf SQUIDs in cardiology.     

一种识别混沌时间序列动力学异同性的方法

定义了两个新的统计量，分别记为Q和R，Q称为动力学自相关因子指数，R称为动力学互相关 因子指数.用Q和R对不同时间序列的动力学“距离”或同一时间序列中不同区段（窗口）的 动力学“距离”进行估算，可以鉴别这些时间序列的动力学属性或它们内在的动力学结构层 次以及复杂性.一些典型实例检验表明，这种方法是有效的. 关键词： 混沌时间序列 动力学自相关因子指数 动力学互相关因子指数