INTRODUCTIONIt has been reported in many studies that electro-acupuncture(EA)can positively regulate erythrocyticimmunity and T-lymphocytic subgroups.Nevertheless,its mechanism remains to be explored.In thepresent stu...INTRODUCTIONIt has been reported in many studies that electro-acupuncture(EA)can positively regulate erythrocyticimmunity and T-lymphocytic subgroups.Nevertheless,its mechanism remains to be explored.In thepresent study,a multi-group,multi-stepped and multi-indexed observation was conducted on the effects of EA展开更多
The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorit...The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.展开更多
仿真耳是听力计量的主要仪器之一,为满足听力计在8~16 k Hz高频范围内的计量需求,须对仿真耳进行高频校准。通过适配器的使用,解决了仿真耳高频校准中存在的测量结果不稳定的问题。同时,针对仿真耳中传声器声压灵敏度级和仿真耳声耦合...仿真耳是听力计量的主要仪器之一,为满足听力计在8~16 k Hz高频范围内的计量需求,须对仿真耳进行高频校准。通过适配器的使用,解决了仿真耳高频校准中存在的测量结果不稳定的问题。同时,针对仿真耳中传声器声压灵敏度级和仿真耳声耦合腔声学特性这两项主要技术指标,建立了8~16 k Hz频率范围内的自动测量系统,对其进行测量。测量结果表明声压灵敏度级的标准偏差小于0.2 d B,表征耦合腔声学特性的频响测量标准偏差小于0.3 d B。展开更多
目的综合比较感音神经性耳聋患者多频稳态听觉诱发电位(auditory steady-state response,ASSR)听域与纯音听域测试(pure tone audiometer,PTA)的差距,分析两种听域评估方法的相关性及其规律。方法比较126例中的198耳感音神经性耳聋的ASS...目的综合比较感音神经性耳聋患者多频稳态听觉诱发电位(auditory steady-state response,ASSR)听域与纯音听域测试(pure tone audiometer,PTA)的差距,分析两种听域评估方法的相关性及其规律。方法比较126例中的198耳感音神经性耳聋的ASSR听域图与PTA的听域图。结果中重度、重度听力损失情况下,从1 k Hz到4 k Hz声刺激时,ASSR听域与PTA听域比较接近,差异无统计学意义(P>0.05)。除外4 k Hz声刺激时,轻度耳聋患者的ASSR听域显著高于PTA听域(P<0.05)。而在0.5 k Hz声刺激时,只有重度听力损失的ASSR听域与PTA听域接近(P>0.05)。结论应用ASSR评估实际听域时应结合临床听力损失程度及声刺激频率。展开更多
Electromagnetic Radiation Source Identification(ERSI) is a key technology that is widely used in military and radiation management and in electromagnetic interference diagnostics.The discriminative capability of machi...Electromagnetic Radiation Source Identification(ERSI) is a key technology that is widely used in military and radiation management and in electromagnetic interference diagnostics.The discriminative capability of machine learning methods has recently been used for facilitating ERSI.This paper presents a new approach to improve ERSI by adopting support vector machines,which are proven to be effective tools in pattern classification and regression,on the basis of the spatial distribution of electromagnetic radiation sources.Spatial information is converted from 3D cubes to 1D vectors with subscripts as inputs in order to simplify the model.The model is trained with 187 500 data sets in order to enable it to identify the types of radiation source types with an accuracy of up to 99.9%.The influence of parameters(e.g.,penalty parameter,reflection and noise from the ambient environment,and the scaling method for the input data) are discussed.The proposed method has good performance in noisy and reverberant environment.It has an identification accuracy of 82.15% when the signal-to-noise ratio is 20 dB.The proposed method has better accuracy in a noisy environment than artificial neural networks.Given that each Electromagnetic(EM) source has unique spatial characteristics,this method can be used for EM source identification and EM interference diagnostics.展开更多
基金the National Natural Science Foundation of China,№39970888.
文摘INTRODUCTIONIt has been reported in many studies that electro-acupuncture(EA)can positively regulate erythrocyticimmunity and T-lymphocytic subgroups.Nevertheless,its mechanism remains to be explored.In thepresent study,a multi-group,multi-stepped and multi-indexed observation was conducted on the effects of EA
基金Project(50905037) supported by the National Natural Science Foundation of ChinaProject(20092304120014) supported by Specialized Research Fund for the Doctoral Program of Higher Education of China+2 种基金 Project(20100471021) supported by the China Postdoctoral Science Foundation Project(LBH-Q09134) supported by Heilongjiang Postdoctoral Science-Research Foundation,China Project (HEUFT09013) supported by the Foundation of Harbin Engineering University,China
文摘The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.
文摘仿真耳是听力计量的主要仪器之一,为满足听力计在8~16 k Hz高频范围内的计量需求,须对仿真耳进行高频校准。通过适配器的使用,解决了仿真耳高频校准中存在的测量结果不稳定的问题。同时,针对仿真耳中传声器声压灵敏度级和仿真耳声耦合腔声学特性这两项主要技术指标,建立了8~16 k Hz频率范围内的自动测量系统,对其进行测量。测量结果表明声压灵敏度级的标准偏差小于0.2 d B,表征耦合腔声学特性的频响测量标准偏差小于0.3 d B。
文摘目的综合比较感音神经性耳聋患者多频稳态听觉诱发电位(auditory steady-state response,ASSR)听域与纯音听域测试(pure tone audiometer,PTA)的差距,分析两种听域评估方法的相关性及其规律。方法比较126例中的198耳感音神经性耳聋的ASSR听域图与PTA的听域图。结果中重度、重度听力损失情况下,从1 k Hz到4 k Hz声刺激时,ASSR听域与PTA听域比较接近,差异无统计学意义(P>0.05)。除外4 k Hz声刺激时,轻度耳聋患者的ASSR听域显著高于PTA听域(P<0.05)。而在0.5 k Hz声刺激时,只有重度听力损失的ASSR听域与PTA听域接近(P>0.05)。结论应用ASSR评估实际听域时应结合临床听力损失程度及声刺激频率。
基金supported by the National Natural Science Foundation of China under Grant No.61201024
文摘Electromagnetic Radiation Source Identification(ERSI) is a key technology that is widely used in military and radiation management and in electromagnetic interference diagnostics.The discriminative capability of machine learning methods has recently been used for facilitating ERSI.This paper presents a new approach to improve ERSI by adopting support vector machines,which are proven to be effective tools in pattern classification and regression,on the basis of the spatial distribution of electromagnetic radiation sources.Spatial information is converted from 3D cubes to 1D vectors with subscripts as inputs in order to simplify the model.The model is trained with 187 500 data sets in order to enable it to identify the types of radiation source types with an accuracy of up to 99.9%.The influence of parameters(e.g.,penalty parameter,reflection and noise from the ambient environment,and the scaling method for the input data) are discussed.The proposed method has good performance in noisy and reverberant environment.It has an identification accuracy of 82.15% when the signal-to-noise ratio is 20 dB.The proposed method has better accuracy in a noisy environment than artificial neural networks.Given that each Electromagnetic(EM) source has unique spatial characteristics,this method can be used for EM source identification and EM interference diagnostics.
