信息识别与分类中的信号处理算法研究
|
摘要
模式识别能力是人类智能的重要组成部分。用计算机实现模式的自动识别,是开发智能机器的一个最关键的突破口。模式识别不仅是一个有重大科学意义的研究领域,也是数字化网络时代诸多实际应用需要突破的一项重大关键技术。
尽管人们对模式识别分类算法的研究已从事了很长时间,并已取得了很多成果,但到目前为止,机器的识别本领还无法与人的认知能力相比,这仍是一个有难度的开放问题,因此它们对于模式识别等学科和理论来说,仍有较强的研究价值和意义。同时,模式识别分类算法的研究,对于进一步提高复杂环境条件下的文字识别、语音识别、指纹识别、遥感、医学诊断、工业产品检测、天气预测、卫星航空图片等领域的技术和应用问题,都具有重要的借鉴和启发意义。
本文结合作者在计算机视频电磁泄漏文字图像分类识别、血容积脉波采样数据分类等应用方向的研究工作,系统得阐述了统计模式识别系统的构成,追踪了目前模式识别热门应用中常用的关键技术,着重研究了信息分类与识别算法的主要技术与应用。同时,实现了关键技术在新实例上的应用,设计了计算机视频电磁泄漏文字图像识别系统和血容积脉波采样数据分类系统,针对相应的实现在原有技术上进行了改进,取得了很好的效里。
模式识别的三个关键技术是样品的预处理、特征提取和选择、以及分类器设计。本文主要围绕以下几点开展了研究工作：第一,将迭代阈值法用于计算机电磁泄漏文字图像的二值化,获得了更好的去噪效果；第二,利用盲信号处理技术(如PCA、FastICA、Infomax等)提取血容积脉波采样数据的特征,研究表明经FastICA特征提取后的分类结果更准确；第三,将基于概率统计的贝叶斯分类算法和支持向量机方法设计的分类器,分别应用于计算机视频电磁泄漏文字图像识别系统和血容积脉波采样数据分类系统,并取得了很好的效果,为这两个领域的进一步研究打下了良好的基础；第四,研究了小型化遥测胶囊微带天线的设计。
本文的主要贡献和创新性有：
针对电磁泄漏文字图像预处理中的问题,系统采用一种快速迭代阈值方法作为预处理手段,并将传统的基于概率统计的贝叶斯分类算法应用在电磁泄漏文字图像识别中,并得到了很好的识别效果；研究了血容积脉波采样数据分类的特征提取部分,采用了盲信号处理算法进行特征提取,提出了应用支持向量机分类算法对血容积脉波采样数据分类,成功地实现了正确分类。另外,作者还针对小型化的遥测胶囊微带天线,研究了T型DGS结构参数变化对其频率特性的影响。经过仿真分析,证明了基于缺陷接地结构的遥测胶囊微带天线能够成功地抑制高次谐波,并提高辐射特性。
The capability of Pattern recognition is an important part of human intelligence. Realizing the automatic pattern recognition by computer is a key breakthrough of intelligence machine developing. Pattern recognition is not only a research field having great scientific value, but also a great key technique which we need to break through in many applications of the digital network times.
Despite the classification algorithm for pattern recognition research has been engaged in a long time and has achieved many results, but so far, the machine identification of skills not yet in comparison with the human cognitive abilities, this is still a difficult open issue, so they and other subjects and theories for pattern recognition is still a strong research value and significance. At the same time, pattern recognition classification algorithm research to further enhance the complex environmental conditions of the text recognition, speech recognition, fingerprint recognition, remote sensing, medical diagnostics, industrial inspection, weather forecasts, satellite images and other areas of aviation technology and application issues are an important reference and instructive.
Integrating the research work of some application direction, such as classification and recognition of electromagnetic leakage of computer video text image and blood volume pulse sampled-data classification, this paper systematic describes the composition of the statistics pattern recognition system, traces the key techniques which are widely used in many hot application, focuses on information classification and recognition algorithm for a major technology and applications. Meanwhile, the realization of a key technology in the new instance of the application, the design of electromagnetic leakage of computer video image recognition system and blood volume pulse sampled-data classification system for the corresponding realization of the original technology has been improved and achieved a very good effect.
Preprocessing, feature extraction and selection, classifier design are three key techniques of pattern recognition. In this paper, a study conducted around the following work:The first, the iterative threshold method was used in computer electromagnetic leakage of the text image binarization to obtain a better de-noising effect; The second, the use of blind signal processing techniques (such as PCA, FastICA, Infomax, etc.) to extract the blood volume pulse characteristics of sampled data, studies show that features extracted by the FastICA make the classification results more accurate; The third, Bayesian probability and statistics-based classification algorithm and support vector machine classifiers was respectively applied to the computer electromagnetic leakage of video image recognition system and blood volume pulse sampled-data classification system, and have achieved very good results, which laid a good foundation for the further research of these two areas; Finally, studied on the design of a novel telemetry capsule microstrip antennas.
The main contribution and innovation of this paper include:
Aiming at the preprocessing problems of electromagnetic leakage text image, we purposed an iterative threshold method as a pretreatment means, and the traditional Bayesian probability and statistics-based classification algorithm was applied to an innovative image recognition in the text of electromagnetic leakage and get a good recognition results; basing on the research of blood volume pulse sampled-data classification, we purposed some blind signal process methods to select features, combined with support vector machine classification algorithm, which achieved a successful classification result. In addition, we also designed a novel defected ground structure and applicated it on telemetry capsule microstrip antennas. The simulated results show that the high order harmonics of microstrip based on DGS could be restrained successfully and radiation character is improved.
尽管人们对模式识别分类算法的研究已从事了很长时间,并已取得了很多成果,但到目前为止,机器的识别本领还无法与人的认知能力相比,这仍是一个有难度的开放问题,因此它们对于模式识别等学科和理论来说,仍有较强的研究价值和意义。同时,模式识别分类算法的研究,对于进一步提高复杂环境条件下的文字识别、语音识别、指纹识别、遥感、医学诊断、工业产品检测、天气预测、卫星航空图片等领域的技术和应用问题,都具有重要的借鉴和启发意义。
本文结合作者在计算机视频电磁泄漏文字图像分类识别、血容积脉波采样数据分类等应用方向的研究工作,系统得阐述了统计模式识别系统的构成,追踪了目前模式识别热门应用中常用的关键技术,着重研究了信息分类与识别算法的主要技术与应用。同时,实现了关键技术在新实例上的应用,设计了计算机视频电磁泄漏文字图像识别系统和血容积脉波采样数据分类系统,针对相应的实现在原有技术上进行了改进,取得了很好的效里。
模式识别的三个关键技术是样品的预处理、特征提取和选择、以及分类器设计。本文主要围绕以下几点开展了研究工作：第一,将迭代阈值法用于计算机电磁泄漏文字图像的二值化,获得了更好的去噪效果；第二,利用盲信号处理技术(如PCA、FastICA、Infomax等)提取血容积脉波采样数据的特征,研究表明经FastICA特征提取后的分类结果更准确；第三,将基于概率统计的贝叶斯分类算法和支持向量机方法设计的分类器,分别应用于计算机视频电磁泄漏文字图像识别系统和血容积脉波采样数据分类系统,并取得了很好的效果,为这两个领域的进一步研究打下了良好的基础；第四,研究了小型化遥测胶囊微带天线的设计。
本文的主要贡献和创新性有：
针对电磁泄漏文字图像预处理中的问题,系统采用一种快速迭代阈值方法作为预处理手段,并将传统的基于概率统计的贝叶斯分类算法应用在电磁泄漏文字图像识别中,并得到了很好的识别效果；研究了血容积脉波采样数据分类的特征提取部分,采用了盲信号处理算法进行特征提取,提出了应用支持向量机分类算法对血容积脉波采样数据分类,成功地实现了正确分类。另外,作者还针对小型化的遥测胶囊微带天线,研究了T型DGS结构参数变化对其频率特性的影响。经过仿真分析,证明了基于缺陷接地结构的遥测胶囊微带天线能够成功地抑制高次谐波,并提高辐射特性。
The capability of Pattern recognition is an important part of human intelligence. Realizing the automatic pattern recognition by computer is a key breakthrough of intelligence machine developing. Pattern recognition is not only a research field having great scientific value, but also a great key technique which we need to break through in many applications of the digital network times.
Despite the classification algorithm for pattern recognition research has been engaged in a long time and has achieved many results, but so far, the machine identification of skills not yet in comparison with the human cognitive abilities, this is still a difficult open issue, so they and other subjects and theories for pattern recognition is still a strong research value and significance. At the same time, pattern recognition classification algorithm research to further enhance the complex environmental conditions of the text recognition, speech recognition, fingerprint recognition, remote sensing, medical diagnostics, industrial inspection, weather forecasts, satellite images and other areas of aviation technology and application issues are an important reference and instructive.
Integrating the research work of some application direction, such as classification and recognition of electromagnetic leakage of computer video text image and blood volume pulse sampled-data classification, this paper systematic describes the composition of the statistics pattern recognition system, traces the key techniques which are widely used in many hot application, focuses on information classification and recognition algorithm for a major technology and applications. Meanwhile, the realization of a key technology in the new instance of the application, the design of electromagnetic leakage of computer video image recognition system and blood volume pulse sampled-data classification system for the corresponding realization of the original technology has been improved and achieved a very good effect.
Preprocessing, feature extraction and selection, classifier design are three key techniques of pattern recognition. In this paper, a study conducted around the following work:The first, the iterative threshold method was used in computer electromagnetic leakage of the text image binarization to obtain a better de-noising effect; The second, the use of blind signal processing techniques (such as PCA, FastICA, Infomax, etc.) to extract the blood volume pulse characteristics of sampled data, studies show that features extracted by the FastICA make the classification results more accurate; The third, Bayesian probability and statistics-based classification algorithm and support vector machine classifiers was respectively applied to the computer electromagnetic leakage of video image recognition system and blood volume pulse sampled-data classification system, and have achieved very good results, which laid a good foundation for the further research of these two areas; Finally, studied on the design of a novel telemetry capsule microstrip antennas.
The main contribution and innovation of this paper include:
Aiming at the preprocessing problems of electromagnetic leakage text image, we purposed an iterative threshold method as a pretreatment means, and the traditional Bayesian probability and statistics-based classification algorithm was applied to an innovative image recognition in the text of electromagnetic leakage and get a good recognition results; basing on the research of blood volume pulse sampled-data classification, we purposed some blind signal process methods to select features, combined with support vector machine classification algorithm, which achieved a successful classification result. In addition, we also designed a novel defected ground structure and applicated it on telemetry capsule microstrip antennas. The simulated results show that the high order harmonics of microstrip based on DGS could be restrained successfully and radiation character is improved.
引文
[1]ZHANG Hongxin, LU Yinghua, HE Pengfei, WANG Haixia. Text Recovery from EM Leakage of computers. Journal of Southwest Jiaotong University,2007, Vol.42, NO.6, pp 653-657
[2]Huang, B, Yan, G.Z, and Zan, P. Design of ingested small microstrip antenna for radiotelemetry capsules[J]. Electronics Letters, Oct.25 2007,43
[3]Vapnik V N. The Nature of Statistical Learning Theory, NY:Springer-Verlag,1995
[4]Cortes C, Vapnik V N. Support vector networks [J]. Machine Learning,1995,20(3): 273-297
[5]李伟,统计模式识别系统中关键算法的研究与应用,[学位论文],中国优秀硕士学位论文全文数据库,CNKI, 2008
[6]戴智康.新一代信函分拣机一OVCS邮政管理与技术.1994,(4)：13-15
[7]Sankur B,Sezgin M.Image Thresholding Techniquesa.Digital Object Identifier, 1995,8(3):385～389
[8]胡必锦.标准汉字的自动识别.重庆交通学院学报.2006.8 25(4)：154～157
[9]Mallat S,Zhang Z.Matching Pursuit with Time-Frequency Dictionaries[J],IEEE Trans.On Signal Processing,1993,41 (12):3397-3415
[10]傅霆,尧德中.稀疏分解的加权迭代方法及其初步应用[J].电子学报,2004,32(4)：567-570
[11]廖斌.基于匹配跟踪的低速率视频编码[D],博士学位论文,北京：中国科学院研究生院(软件研究所),2003.7
[12]Gribonval Remi,Bacry,Emmanuel.Harmonic Decomposition of Audio Signals with Matching Pursuit[J].IEEE Transaction on Signal Processing,2003,1,1(51):101-111
[13]Liu B,Ling S.F.,Gribonval R.Bearing Failure Detection Using Matching Pursuit[J].NDT and E International,2002,6,4(35):255-262
[14]Arthur P L, Philipos C L.Voiced/unvoiced Speech Discrimination in Noise Using Gabor Atomic Decomposition[A].Proc.of IEEE ICASSP[C], Hong Kong,2003,4 (1):820-828
[15]Gribonval R.,(IRCAM),Bacry E.,Mallat S,Depalle Ph.,Rodet X.Analysis of Sound Signals with High Resolution Matching Pursuit[A].Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis[C],1996:125-128
[16]Bergeau F.,Mallat S.Matching Pursuit of Images[A].Proceedings of IEEE-SP,Oct,1994: 330-333
[17]ChoudhuryA.Rahman, Wael Badawy, Ahmad Radmanesh, AReal Time Vehicle's License's Plate Reeognition System, Proeeedings of the IEEE Conference on Advanced Video and Signal Based Surveillance(AVSS'03)
[18]边肇棋,张学工,模式识别,北京：清华大学出版社,2000,250～251
[19]K.Fukunaga, Introduction to Statistical Pattern Recognition, second ed. Academic Press, 1990
[20]边肇棋,张学工,模式识别,清华大学出版社,2000,252～253
[21]Vapnik V N.The Nature of Statistical of Learning Theory.New York:Springer2Verlag, 1995
[22]杜树新,吴铁军.模式识别中的支持向量机方法.浙江大学学报,2003,37(5)
[23]Edgar Osuna,Robert Freund,Federico Girosi.Training support vector machines an application to face detection.CVPR'97,1997
[24]杨淑莹.模式识别与智能计算—Matlab技术实现.电子工业出版社.2008.
[25]W.L.Stutzman, G.A. Thiele. Antenna theory and design. John Wiley & Sons, Inc.,1998
[26]钟顺时.微带天线理论与应用.西安：西安电子科技大学出版社,1991
[27]John, S. Strong localization of photons in certain disordered dielectric superlattices[J]. Physical Review Letters,1987,58(23):2486-2489
[28]Yablonovitch, E. Inhibited Spontaneous Emission in Solid-State Physics and Electronics[J]. Physical Review Letters,1987,58(20):2059-2062
[29]Jong-Im, P., P. Jong-Im, K. Chul-Soo,et al. Modeling of a photonic bandgap and its application for the low-pass filter design[C]. Microwave Conference, Asia Pacific,1999,2: 331-334
[30]Dal Ahn,Jun-Seok Park,Chul-Soo Kim,Juno Kim,Yongxi Qian,Tatsuo Itoh,A design of the low-pass filter using the novel microstrip defected ground structure,IEEE transactions on microwave theory and techniques,VOL.49,NO.1,January 2001,pp.86-93
[31]C. S. Kim, J.s.Park,A. Ahn,et al.A novel 1-D periodic defected ground structure for planar circuits. IEEE Microwave and Guided Wave Lett. [J],2000,10(4):131-133
[32]J. Lim, C. Kim, Y. Lee. et al. A Spiral-shaped defected ground structure for coplanar waveguide. IEEE Microwave and Guided Wave Lett.[J], 2002,12(9):330-332
[33]J.S.lim,et al. A power amplifier with efficiency improved using defected ground strucrure[J], IEEE Microwave and Guided Wave Lett, 2001,11(4):170-172
[34]J. Lim, Y. Jeong, Dal Ahn et al. Improvement in performance of power amplifiers by defected ground structure[J], IEICE Tran. on Electronics,2004, E87-C(1):60-65
[35]S. G. Jeong, D,K. Hwang, Y. C. Jeong,et al. Amplifier design λ/4 high impedance bias line with defected ground structure(DGS)[C], IEEE. MTT-S,2002.2:1161-1164, Kanagawa
[36]Y. Lee, J. Lim,S. Kim,et al Application of CPW based spiral-shaped defected ground structure to the reduction of phase noise in V-band NIMIC oscillator[C], IEEE MTT-S,2003,3:2253-2256, Philadelphia
[37]Lim J S, Lee S W, Kim C S, et al. A 4.1 unequal Wilkinson power divider [J]. IEEE Transaction on Microwave and Wireless Components Letters,2001,11 (3):124-126
[38]Lim J S, Lee S W, Kim C S, et al. A power amplifier with efficiency improved using defected ground structure[J]. IEEE Transaction on Microwave and Wireless Components Letters,2001,11 (4):170-172
[39]Lim J S, Kim C S, Dal Ahn, et al. Design of low-pass filters using defected ground structure[J]. IEEE Transaction on Microwave Theory and Techiniques,2005, 53(8):2539-2545
[40]CST MICROWAVE STUDIO 5培训教程.北京理工大学CST培训中心,2004.5
[41]Weiland T. Computer modelling of two-and three-dimensional cavit ies[J]. IEEE Trans Nucl Sci,1985, NS-32 (5):2738-2742
[42]Kamigaito O, Go to A, et al. Beam matching section in the new injector for RILAC[J]. RIKEN Accel Prog R ep,1997,30:191-192
[43]栗换彩,基于缺陷接地结构的微带天线特性分析[D].中国优秀硕士学位论文全文数据库,天津大学,2006,3
[44]黄标,颜国正,咎鹏,李倩如,遥测胶囊微带天线的设计[J].上海交通大学学报,2007, vol.11(2):63-67
[45]曹锐,阎跃鹏,合肥工业大学学报(自然科学版),2008,No.9：1830-1833.
[46]应莹,李媛,栗换彩,电子测量技术,Electronic Measurement Technology, 2006,No.6:9-11
[2]Huang, B, Yan, G.Z, and Zan, P. Design of ingested small microstrip antenna for radiotelemetry capsules[J]. Electronics Letters, Oct.25 2007,43
[3]Vapnik V N. The Nature of Statistical Learning Theory, NY:Springer-Verlag,1995
[4]Cortes C, Vapnik V N. Support vector networks [J]. Machine Learning,1995,20(3): 273-297
[5]李伟,统计模式识别系统中关键算法的研究与应用,[学位论文],中国优秀硕士学位论文全文数据库,CNKI, 2008
[6]戴智康.新一代信函分拣机一OVCS邮政管理与技术.1994,(4)：13-15
[7]Sankur B,Sezgin M.Image Thresholding Techniquesa.Digital Object Identifier, 1995,8(3):385～389
[8]胡必锦.标准汉字的自动识别.重庆交通学院学报.2006.8 25(4)：154～157
[9]Mallat S,Zhang Z.Matching Pursuit with Time-Frequency Dictionaries[J],IEEE Trans.On Signal Processing,1993,41 (12):3397-3415
[10]傅霆,尧德中.稀疏分解的加权迭代方法及其初步应用[J].电子学报,2004,32(4)：567-570
[11]廖斌.基于匹配跟踪的低速率视频编码[D],博士学位论文,北京：中国科学院研究生院(软件研究所),2003.7
[12]Gribonval Remi,Bacry,Emmanuel.Harmonic Decomposition of Audio Signals with Matching Pursuit[J].IEEE Transaction on Signal Processing,2003,1,1(51):101-111
[13]Liu B,Ling S.F.,Gribonval R.Bearing Failure Detection Using Matching Pursuit[J].NDT and E International,2002,6,4(35):255-262
[14]Arthur P L, Philipos C L.Voiced/unvoiced Speech Discrimination in Noise Using Gabor Atomic Decomposition[A].Proc.of IEEE ICASSP[C], Hong Kong,2003,4 (1):820-828
[15]Gribonval R.,(IRCAM),Bacry E.,Mallat S,Depalle Ph.,Rodet X.Analysis of Sound Signals with High Resolution Matching Pursuit[A].Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis[C],1996:125-128
[16]Bergeau F.,Mallat S.Matching Pursuit of Images[A].Proceedings of IEEE-SP,Oct,1994: 330-333
[17]ChoudhuryA.Rahman, Wael Badawy, Ahmad Radmanesh, AReal Time Vehicle's License's Plate Reeognition System, Proeeedings of the IEEE Conference on Advanced Video and Signal Based Surveillance(AVSS'03)
[18]边肇棋,张学工,模式识别,北京：清华大学出版社,2000,250～251
[19]K.Fukunaga, Introduction to Statistical Pattern Recognition, second ed. Academic Press, 1990
[20]边肇棋,张学工,模式识别,清华大学出版社,2000,252～253
[21]Vapnik V N.The Nature of Statistical of Learning Theory.New York:Springer2Verlag, 1995
[22]杜树新,吴铁军.模式识别中的支持向量机方法.浙江大学学报,2003,37(5)
[23]Edgar Osuna,Robert Freund,Federico Girosi.Training support vector machines an application to face detection.CVPR'97,1997
[24]杨淑莹.模式识别与智能计算—Matlab技术实现.电子工业出版社.2008.
[25]W.L.Stutzman, G.A. Thiele. Antenna theory and design. John Wiley & Sons, Inc.,1998
[26]钟顺时.微带天线理论与应用.西安：西安电子科技大学出版社,1991
[27]John, S. Strong localization of photons in certain disordered dielectric superlattices[J]. Physical Review Letters,1987,58(23):2486-2489
[28]Yablonovitch, E. Inhibited Spontaneous Emission in Solid-State Physics and Electronics[J]. Physical Review Letters,1987,58(20):2059-2062
[29]Jong-Im, P., P. Jong-Im, K. Chul-Soo,et al. Modeling of a photonic bandgap and its application for the low-pass filter design[C]. Microwave Conference, Asia Pacific,1999,2: 331-334
[30]Dal Ahn,Jun-Seok Park,Chul-Soo Kim,Juno Kim,Yongxi Qian,Tatsuo Itoh,A design of the low-pass filter using the novel microstrip defected ground structure,IEEE transactions on microwave theory and techniques,VOL.49,NO.1,January 2001,pp.86-93
[31]C. S. Kim, J.s.Park,A. Ahn,et al.A novel 1-D periodic defected ground structure for planar circuits. IEEE Microwave and Guided Wave Lett. [J],2000,10(4):131-133
[32]J. Lim, C. Kim, Y. Lee. et al. A Spiral-shaped defected ground structure for coplanar waveguide. IEEE Microwave and Guided Wave Lett.[J], 2002,12(9):330-332
[33]J.S.lim,et al. A power amplifier with efficiency improved using defected ground strucrure[J], IEEE Microwave and Guided Wave Lett, 2001,11(4):170-172
[34]J. Lim, Y. Jeong, Dal Ahn et al. Improvement in performance of power amplifiers by defected ground structure[J], IEICE Tran. on Electronics,2004, E87-C(1):60-65
[35]S. G. Jeong, D,K. Hwang, Y. C. Jeong,et al. Amplifier design λ/4 high impedance bias line with defected ground structure(DGS)[C], IEEE. MTT-S,2002.2:1161-1164, Kanagawa
[36]Y. Lee, J. Lim,S. Kim,et al Application of CPW based spiral-shaped defected ground structure to the reduction of phase noise in V-band NIMIC oscillator[C], IEEE MTT-S,2003,3:2253-2256, Philadelphia
[37]Lim J S, Lee S W, Kim C S, et al. A 4.1 unequal Wilkinson power divider [J]. IEEE Transaction on Microwave and Wireless Components Letters,2001,11 (3):124-126
[38]Lim J S, Lee S W, Kim C S, et al. A power amplifier with efficiency improved using defected ground structure[J]. IEEE Transaction on Microwave and Wireless Components Letters,2001,11 (4):170-172
[39]Lim J S, Kim C S, Dal Ahn, et al. Design of low-pass filters using defected ground structure[J]. IEEE Transaction on Microwave Theory and Techiniques,2005, 53(8):2539-2545
[40]CST MICROWAVE STUDIO 5培训教程.北京理工大学CST培训中心,2004.5
[41]Weiland T. Computer modelling of two-and three-dimensional cavit ies[J]. IEEE Trans Nucl Sci,1985, NS-32 (5):2738-2742
[42]Kamigaito O, Go to A, et al. Beam matching section in the new injector for RILAC[J]. RIKEN Accel Prog R ep,1997,30:191-192
[43]栗换彩,基于缺陷接地结构的微带天线特性分析[D].中国优秀硕士学位论文全文数据库,天津大学,2006,3
[44]黄标,颜国正,咎鹏,李倩如,遥测胶囊微带天线的设计[J].上海交通大学学报,2007, vol.11(2):63-67
[45]曹锐,阎跃鹏,合肥工业大学学报(自然科学版),2008,No.9：1830-1833.
[46]应莹,李媛,栗换彩,电子测量技术,Electronic Measurement Technology, 2006,No.6:9-11