计算机科学 ›› 2015, Vol. 42 ›› Issue (Z11): 550-553.

• 智能系统及应用 • 上一篇    下一篇

基于蚁群算法的带截止区均匀量化器的优化及其在ECG数据压缩中的应用

王伟平,杨苗   

  1. 昆明理工大学城市学院 昆明650093,云南省产品质量监督检验研究院 昆明650223
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受云南省教育厅面上项目:基于RFID与GPRS技术的灾难救援系统开发研究(KKJA201025051),云南省软件工程重点实验室开放基金资助

USDZQ Optimization Based on Ant Colony Algorithm and Application in ECG Compression

WANG Wei-ping and YANG Miao   

  • Online:2018-11-14 Published:2018-11-14

摘要: 结合小波系数的特点,采用了改进的均匀量化器——带截止区的均匀量化器(USDZQ)对变换后的小波系数进行量化。量化器的参数选取直接影响到ECG数据压缩的质量和压缩比,因此重点研究了USDZQ的参数优化问题,选取了蚁群优化算法(ACO)作为USDZQ参数的优化工具。最后,利用本文算法对MIT-BIH心律失常数据库的ECG信号进行了编码测试。实验结果表明,只要对USDZQ的参数进行合理优化,USDZQ就能获得优于均匀量化的性能,并可以成功地应用于ECG数据压缩中。

关键词: 蚁群优化算法,带截止区的均匀量化器,ECG压缩

Abstract: This paper adopted an improved uniform quantizer,a uniform scalar dead zone quantizer(USDZQ),to quantize the transformed coefficients.The selection of quantizer parameters directly affects the ECG data compression performance.Therefore the objective of this study was focused on the optimization of the USDZQ parameters.We used the ant colony optimization(ACO) algorithm for the optimization.Experiments on several records from the MIT-BIH arrhythmia database show that as long as the USDZQ parameter is optimized reasonably,USDZQ can achieve better performance than the uniform quantizer,and may successfully be applied in the ECG data compression.

Key words: ACO,USDZQ,ECG data compression

[1] Colorm A,Dorigo M,Manieaao V.Distributed optimization by ant colonies[C]∥Proc of the First European Conf.on Artificial Life,Paris,France Elsevier Publishing.1991:134-142
[2] Colorni A,et al.Ant system for job-shop scheduling[J].JORBEL,1994,4(1):39-53
[3] Costa D,Hertz A.Ant can color graphs[J].Journal of the Opnl Res Soc,1997,8(3):295-305
[4] Bullnheimer B,Hartl R F,Strauss C.An improved ant system algorithm for the vehicle routing problem[J].Annals of Operations Research,1999,9:319-328
[5] Coello C A C,Cutierrez R L Z,Garcia B M,et al.Automatec design of combinational logic circuits using the Ant Systm[J].Engineering Optimization,2002,4(2):109-127
[6] Cordone R,Maffioli F.Coloured ant system and local search to design local telecommunication networks[J].Applications of Evolutionary Computing,2001,7:60-69
[7] 张纪会,徐心和.具有变异特征的蚁群算法[J].计算机研究与发展,1999,6(10):1240-1245
[8] 马良,项培军.蚂蚁算法在组合优化中的应用[J].管理科学学报,2001,4(2):32-37
[9] 刘康,余玲.蚁群算法及其连续优化算法初析[J].四川轻化工学院学报,2004,17(1):42-46
[10] Batista L V,Carvalho L C,Melcher E U K.Compression of ECG Signals Based on Optimum Quantization of Discrete Cosine Transform Coefficients and Golomb-rice Codeing[C]∥Procee-dings of the 25th Annual International Conference of the IEEE EMBS Cancun.Mexico*September 2003:17-21
[11] Batista L V,Melcher E U K,Carvalho L C.Compression of ECG signals by optimized quantization of discrete cosine transform coefficients[J].Medical Engineering&Physics,2001(23):127-134
[12] Lu Zhi-tao,Kim D Y,Pearlman W A.Wavelet Compression of ECG Signals by the Set Partitioning in Hierarchical Trees Algorithm[J].IEEE Trans.Biomed.Eng.,2000,47(7):849-856
[13] Hilton M L.Wavelet and wavelet packet compression of electrocardiograms[J].IEEE Trans.Biomed.Eng., 1997,44:394-402
[14] Djohan A,Nguyen T Q,Tompkins W J.ECG compression using discrete symmetric wavelet transform[J].IEEE 17th Annual Conference on Engineering in Medicine and Biology Society,1995:167-168
[15] Zigel Y,Cohen A,Abu-ful A,et al.Analysis by synthesis ECG signal compression[J].Comput.in Cardiol.,1997,24:279-282
[16] 刘波.DNA—蚁群算法在车辆路径优化问题中的应用[J].中国新技术新产品,2015(5):7
[17] 张伟娟,张红梅,陈峰.基于蚁群算法的基因路径预测[J].计算机系统应用,2015(3):280-283
[18] 陈亮,吴更生,吴卫.针对应急救援路径规划的一种改进蚁群算法[J].后勤工程学院学报,2015(1):86-90

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!