高等学校化学学报 ›› 2005, Vol. 26 ›› Issue (11): 2010.

• 研究论文 • 上一篇    下一篇

微流控电泳芯片中化学发光信号的分段门限小波降噪

范军, 梁恒, 石晓强   

  1. 西安交通大学生物医学信息工程教育部重点实验室分离科学研究所, 西安710049
  • 收稿日期:2005-01-17 出版日期:2005-11-10 发布日期:2005-11-10
  • 基金资助:

    国家自然科学基金重大项目(批准号:20299030);国家自然科学基金(批准号:20175015)资助

Segment Threshold Wavelet Denosing of Chemiluminescence Signal from Micro-fluidic Electrophoresis Chip

FAN Jun, LIANG Heng, SHI Xiao-Qiang   

  1. The Key Laboratory of Biomedical Information Engineering of Ministry of Education,Separation Science Institute,Xi'an Jiaotong University,Xi'an 710049,China
  • Received:2005-01-17 Online:2005-11-10 Published:2005-11-10

摘要: 采用分段门限小波降噪(STWD)方法对化学信号中的异方差噪声进行降噪处理.用STWD法和统一门限小波降噪法同时处理两种模拟信号(其中之一包含异方差噪声).结果显示,优化参数的STWD法能够更有效地提高降噪效果.采用STWD法对微流控芯片化学发光检测信号中的异方差噪声进行处理,取得了满意的降噪效果.

关键词: 小波降噪, 分段门限, 异方差噪声, 化学发光检测, 微流控电泳芯片

Abstract: The denoising methods based on wavelet transform have been widely applied to eliminate the noise in the chemical measuring signals.However,the general wavelet-denoising methods do not effectually clear away the heteroscedastic noise in some chemical signals.In this contribution,the segment threshold wavelet denoising(STWD) method is proposed to eliminate the heteroscedastic noise that arises in the chemiluminescence detection signal of micro-fluidic electrophoresis chips.In the STWD,the wavelet denoising thresholds are independently chosen one segment by one segment according to the noise variances.Two synthetic signals(one with the general white noise,another with the heteroscedastic noise) were used to verify the validity of the STWD when the different parameters of wavelet denoising were adopted,and the STWD with optimized parameters was also applied to denoise the chemiluminescence detection signals of micro-fluidic electrophoresis chips.In comparison with the general wavelet denoising method,the STWD showed the better denoising effects in the two synthetic and the chemiluminescence signals.It indicates that the STWD could considerably improve the denoising performance of the signals with heteroscedastic noises.

Key words: Wavelet denoising, Segment threshold, Heteroscedastic noise, Chemiluminescence detection, Micro-fluidic electrophoresis chip

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