基于自适应学习算法的小波消噪在热工过程信号处理中的应用
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摘要
小波变换具有局部性特点,其在信号降噪方面有较强优势。但是,在消噪过程中阈值的选取将直接影响到信号处理效果,而软阈值和硬阈值消噪方法都有不足之处。对此,引入了梯度的自适应学习算法以求取最佳阈值,并将该方法用于处理热工过程信号,为故障诊断和系统辨识提供更接近实际的信号。
The wavelet transform has partial features,and boasting stronger advantage in signal de-noising.However,the threshold value choise in de-noising process will directly affect the result of signal processing,and both of soft and hard threshold value de-noising methods have their deficiencies.For this,an adaptive learning algorithm of gradient has been introduced for seeking the optimal threshold value,and the said method being applied in signal processing of thermal Engineering process,providing signal more nearing to the actual one for fault diagnosis and system identification.
The wavelet transform has partial features,and boasting stronger advantage in signal de-noising.However,the threshold value choise in de-noising process will directly affect the result of signal processing,and both of soft and hard threshold value de-noising methods have their deficiencies.For this,an adaptive learning algorithm of gradient has been introduced for seeking the optimal threshold value,and the said method being applied in signal processing of thermal Engineering process,providing signal more nearing to the actual one for fault diagnosis and system identification.
引文
[1]徐长发.实用小波方法[M].武汉:华中科技大学出版社,2001.
[2]张贤达,保铮.非平稳信号分析与处理[M].北京:国防工业出版社,1998.
[3]刘贵忠,邸双亮.小波分析及其应用[M].西安:西安电子科技大学出版社,1992.
[4]X P Zhang,M Desai.Adaptive Denoising and Based onSURE Risk[J].IEEE Signal Processing Letter,1998,10(5):256-267.
[5]X P Zhang.Thresholding Neural Networks for AdaptiveNoise Reduction[J].IEEE Signal Processing Letter,1998,10(5):265-267.
[6]Barbara B H.The world according to wavelets:the storyof a mathematical technique in the making[Z].A K Pe-ters Ltd.,1998.
[7]Meyer Y.Wavelets:Algorithms&Applications[M].Philadelphia:SIAMPubl,1993.
[8]Donoho D L.De-noising by soft-thresholding[J].IEEETrans.On IT,1995,41(3):613-627.
[9]胡昌华.基于MATLAB的系统分析与设计——小波分析[M].西安:西安电子科技大学出版社.2001.
[10]郑治真.小波变换及其MATLAB工具的应用[M].北京:地震出版社.2001.
[2]张贤达,保铮.非平稳信号分析与处理[M].北京:国防工业出版社,1998.
[3]刘贵忠,邸双亮.小波分析及其应用[M].西安:西安电子科技大学出版社,1992.
[4]X P Zhang,M Desai.Adaptive Denoising and Based onSURE Risk[J].IEEE Signal Processing Letter,1998,10(5):256-267.
[5]X P Zhang.Thresholding Neural Networks for AdaptiveNoise Reduction[J].IEEE Signal Processing Letter,1998,10(5):265-267.
[6]Barbara B H.The world according to wavelets:the storyof a mathematical technique in the making[Z].A K Pe-ters Ltd.,1998.
[7]Meyer Y.Wavelets:Algorithms&Applications[M].Philadelphia:SIAMPubl,1993.
[8]Donoho D L.De-noising by soft-thresholding[J].IEEETrans.On IT,1995,41(3):613-627.
[9]胡昌华.基于MATLAB的系统分析与设计——小波分析[M].西安:西安电子科技大学出版社.2001.
[10]郑治真.小波变换及其MATLAB工具的应用[M].北京:地震出版社.2001.
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