In the research of elastic wave signal detection algorithm, a method based on adaptive wavelet analysis and segmentation threshold processing of the channel noise removal methods is suggested to overcome the effect of...In the research of elastic wave signal detection algorithm, a method based on adaptive wavelet analysis and segmentation threshold processing of the channel noise removal methods is suggested to overcome the effect of noise, which is prcduced by absorption loss, scattering loss, reflection loss and multi-path effect during the elastic wave in the transmission undelgroound. The method helps to realize extraction and recovery of weak signal of elastic wave from the multi-path channel, and simulation study is carded out about wavelet de-noising effects of the elastic wave and obtained satisfactory results.展开更多
By utilizing the capability of high-speed computing,powerful real-time processing of TMS320F2812 DSP,wavelet thresholding denoising algorithm is realized based on Digital Signal Processors.Based on the multi-resolutio...By utilizing the capability of high-speed computing,powerful real-time processing of TMS320F2812 DSP,wavelet thresholding denoising algorithm is realized based on Digital Signal Processors.Based on the multi-resolution analysis of wavelet transformation,this paper proposes a new thresholding function,to some extent,to overcome the shortcomings of discontinuity in hard-thresholding function and bias in soft-thresholding function.The threshold value can be abtained adaptively according to the characteristics of wavelet coefficients of each layer by adopting adaptive threshold algorithm and then the noise is removed.The simulation results show that the improved thresholding function and the adaptive threshold algorithm have a good effect on denoising and meet the criteria of smoothness and similarity between the original signal and denoising signal.展开更多
文摘In the research of elastic wave signal detection algorithm, a method based on adaptive wavelet analysis and segmentation threshold processing of the channel noise removal methods is suggested to overcome the effect of noise, which is prcduced by absorption loss, scattering loss, reflection loss and multi-path effect during the elastic wave in the transmission undelgroound. The method helps to realize extraction and recovery of weak signal of elastic wave from the multi-path channel, and simulation study is carded out about wavelet de-noising effects of the elastic wave and obtained satisfactory results.
文摘By utilizing the capability of high-speed computing,powerful real-time processing of TMS320F2812 DSP,wavelet thresholding denoising algorithm is realized based on Digital Signal Processors.Based on the multi-resolution analysis of wavelet transformation,this paper proposes a new thresholding function,to some extent,to overcome the shortcomings of discontinuity in hard-thresholding function and bias in soft-thresholding function.The threshold value can be abtained adaptively according to the characteristics of wavelet coefficients of each layer by adopting adaptive threshold algorithm and then the noise is removed.The simulation results show that the improved thresholding function and the adaptive threshold algorithm have a good effect on denoising and meet the criteria of smoothness and similarity between the original signal and denoising signal.
