基于测试仪器的波形识别研究
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摘要
本文针对测试仪器发展中的智能化要求,在对采集信号进行奇异点的检测和消除、去噪等预处理的基础之上,提出了运用差分、均值的方法提取波形识别的特征信息。并用BP算法进行波形识别的实现。最后给出了一种较为典型的失真波形的仿真实验。仿真结果表明该方法能取得较为有效的识别结果。
As concerned to the intelligence demand of test instrument's development, after finding out and eliminating singular data points from all kinds of acquisition data points and eliminating noise from signal and other signal processing methods, this paper presented a feature extraction method from waveform data through numerical difference and numerical average. The goal of waveform recognition can be achieved by applying the BP algorithm to identify the type of waveform. In the subsequent simulating experiments of one typically distorted waveform, the result of waveform recognition is proved to be very satisfactory.
As concerned to the intelligence demand of test instrument's development, after finding out and eliminating singular data points from all kinds of acquisition data points and eliminating noise from signal and other signal processing methods, this paper presented a feature extraction method from waveform data through numerical difference and numerical average. The goal of waveform recognition can be achieved by applying the BP algorithm to identify the type of waveform. In the subsequent simulating experiments of one typically distorted waveform, the result of waveform recognition is proved to be very satisfactory.
引文
[1]李建平.小波分析与信号处理．重庆:重庆大学出版社,1997．
[2]Daubechies I. Orthonormal Basis of Compactly Supported Wavelets．Com m Pure Applied Math,1998．41:909-996．
[3]袁曾任．人工神经元网络及其应用．北京:清华大学出版社,1999．
[4]郑治真．小波变换及其MATLAB工具的应用．北京:地震出版社,2001.
[2]Daubechies I. Orthonormal Basis of Compactly Supported Wavelets．Com m Pure Applied Math,1998．41:909-996．
[3]袁曾任．人工神经元网络及其应用．北京:清华大学出版社,1999．
[4]郑治真．小波变换及其MATLAB工具的应用．北京:地震出版社,2001.
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