As a relatively new method of processing non-stationary signal with high time-frequency resolution, S transform can be used to analyze the time-frequency characteristics of seismic signals. It has the following charac...As a relatively new method of processing non-stationary signal with high time-frequency resolution, S transform can be used to analyze the time-frequency characteristics of seismic signals. It has the following characteristics: its time-frequency resolution corresponding to the signal frequency, reversible inverse transform, basic wavelet that does not have to meet the permit conditions. We combined the threshold method, proposed the S-transform threshold filtering on the basis of S transform timefrequency filtering, and processed airgun seismic records from temporary stations in "Yangtze Program"(the Anhui experiment). Compared with the results of the bandpass filtering, the S transform threshold filtering can improve the signal to noise ratio(SNR) of seismic waves and provide effective help for first arrival pickup and accurate travel time. The first arrival wave seismic phase can be traced farther continuously, and the Pm seismic phase in the subsequent zone is also highlighted.展开更多
Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster(iTRPC-)ultra-wideband(UWB)systems. Our analysis shows that the bit error rate(BER)performance of iT...Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster(iTRPC-)ultra-wideband(UWB)systems. Our analysis shows that the bit error rate(BER)performance of iTRPC-UWB systems can be significantly improved via integration interval determination(IID)and decision threshold optimization. For this purpose,two modifications can be made at the autocorrelation receiver as follows. Firstly,the IID processing is performed for autocorrelation operation to capture multi-path energy as much as possible. Secondly,adaptive decision threshold(ADT)instead of zero decision threshold(ZDT),is used as estimated optimal decision threshold for symbol detection. Performance of iTRPCUWB systems using IID and ADT was evaluated in realistic IEEE 802.15.4a UWB channel models and the simulation results demonstrated our theoretical analysis.展开更多
In the ultrasonic detection of defects in friction welded joints, it is difficult to exactly detect some weak bonding defects because of the noise pollution. This paper proposed an improved threshold function based on...In the ultrasonic detection of defects in friction welded joints, it is difficult to exactly detect some weak bonding defects because of the noise pollution. This paper proposed an improved threshold function based on the multi-resolution analysis wavelet threshold de-noising method which was put forward by Donoho and Johnstone, and applied this method in the de-noising of the defective signals. This threshold function overcomes the discontinuous shortcoming of the hard-threshold function and the disadvantage of soft threshold function which causes an invariable deviation between the estimated wavelet coeffwients and the decomposed wavelet coefficients. The improved threshold function is of simple expression and convenient for calculation. The actual test results of defect noise signal show that this improved method can get less mean square error （ MSE ） and higher signal-to-noise ratio of reconstructed signals than those calculated from hard threshold and soft threshold methods. The improved threshold function has excellent de-noising effect.展开更多
An important issue of ground-penetrating radar （GPR） signals analysis is de-noising thai is the guarantee of acquiring good detecting effect. The paper illustrates a successful application of digital single process...An important issue of ground-penetrating radar （GPR） signals analysis is de-noising thai is the guarantee of acquiring good detecting effect. The paper illustrates a successful application of digital single processor （DSP） based on wavelet shrinkage algorithm. In order to realize real-time GPP, signals analysis, some key issues are discussed such as the realization of fast wavelet transformation, the selection of CPU chip and the optimization of data movement. Experimenial results show that the DSP based application not only basically meets the real-time requirement of GPP, signals analysis, but also assures the quality of the GPR signals analysis.展开更多
Under the complex condition of nuclear power plant, all kinds of influence factors may cause distortion of on-line monitoring data. It is essential that on-line monitoring data should be de-noised in order to ensure t...Under the complex condition of nuclear power plant, all kinds of influence factors may cause distortion of on-line monitoring data. It is essential that on-line monitoring data should be de-noised in order to ensure the accuracy of diagnosis. Based on the research of wavelet analysis and threshold de-noising, a new threshold denoising method based on Mallat transform is proposed. This method adopts factor weighing method for threshold quantization. Through the specific case of nuclear power plant, it is verified that the algorithm is of validity and superiority.展开更多
The detection of the low-altitude acoustic target is an important way to compensate for the weakness of radar.Removing the noise mixed in acoustic signal as much as possible to retain the useful information is a chall...The detection of the low-altitude acoustic target is an important way to compensate for the weakness of radar.Removing the noise mixed in acoustic signal as much as possible to retain the useful information is a challenging task.Inspired by the wavelet threshold,the de-noising method for low-altitude battlefield acoustic signal based on threshold empirical mode decomposition(EMD-T)is proposed in this paper.Firstly,the noisy signal is decomposed by empirical mode decomposition(EMD)to get the intrinsic mode functions(IMFs).Then the IMFs,whose actual energy exceeds its estimated energy,are processed by the EMD threshold.Finally,the processed IMFs are summed to reconstruct the de-noised signal.To evaluate the performance of the proposed method,extensive simulations are performed using helicopter sound corrupted with four types of typical low-altitude ambient noise under different signal-to-noise ratio(SNR)input values.The performance is evaluated in terms of SNR,root mean square error(RMSE)and smoothness index(SI).The simulations results reveal that the proposed method de-noising method has the perspective of the highest SNR,smallest RMSE and SI in de-noising low-altitude ambient noise compared to other methods,including the wavelet transform(WT)and conventional EMD.展开更多
基金funded by the National Natural Science Foundation Item (41674068)Seismic Youth Funding of GEC (YFGEC2016001)
文摘As a relatively new method of processing non-stationary signal with high time-frequency resolution, S transform can be used to analyze the time-frequency characteristics of seismic signals. It has the following characteristics: its time-frequency resolution corresponding to the signal frequency, reversible inverse transform, basic wavelet that does not have to meet the permit conditions. We combined the threshold method, proposed the S-transform threshold filtering on the basis of S transform timefrequency filtering, and processed airgun seismic records from temporary stations in "Yangtze Program"(the Anhui experiment). Compared with the results of the bandpass filtering, the S transform threshold filtering can improve the signal to noise ratio(SNR) of seismic waves and provide effective help for first arrival pickup and accurate travel time. The first arrival wave seismic phase can be traced farther continuously, and the Pm seismic phase in the subsequent zone is also highlighted.
基金supported in part by the National Natural Science Foundation of China under Grant 61271262,61473047 and 61572083in part by Shaanxi Provincial Natural Science Foundation under Grant 2015JM6310in part by the Special Fund for Basic Scientific Research of Central Colleges,Chang’an University 310824152010 and 0009-2014G1241043
文摘Integration interval and decision threshold issues were investigated for improved transmitted reference pulse cluster(iTRPC-)ultra-wideband(UWB)systems. Our analysis shows that the bit error rate(BER)performance of iTRPC-UWB systems can be significantly improved via integration interval determination(IID)and decision threshold optimization. For this purpose,two modifications can be made at the autocorrelation receiver as follows. Firstly,the IID processing is performed for autocorrelation operation to capture multi-path energy as much as possible. Secondly,adaptive decision threshold(ADT)instead of zero decision threshold(ZDT),is used as estimated optimal decision threshold for symbol detection. Performance of iTRPCUWB systems using IID and ADT was evaluated in realistic IEEE 802.15.4a UWB channel models and the simulation results demonstrated our theoretical analysis.
文摘In the ultrasonic detection of defects in friction welded joints, it is difficult to exactly detect some weak bonding defects because of the noise pollution. This paper proposed an improved threshold function based on the multi-resolution analysis wavelet threshold de-noising method which was put forward by Donoho and Johnstone, and applied this method in the de-noising of the defective signals. This threshold function overcomes the discontinuous shortcoming of the hard-threshold function and the disadvantage of soft threshold function which causes an invariable deviation between the estimated wavelet coeffwients and the decomposed wavelet coefficients. The improved threshold function is of simple expression and convenient for calculation. The actual test results of defect noise signal show that this improved method can get less mean square error （ MSE ） and higher signal-to-noise ratio of reconstructed signals than those calculated from hard threshold and soft threshold methods. The improved threshold function has excellent de-noising effect.
基金Supported by the National Natural Science Founda-tion of China (49984001)
文摘An important issue of ground-penetrating radar （GPR） signals analysis is de-noising thai is the guarantee of acquiring good detecting effect. The paper illustrates a successful application of digital single processor （DSP） based on wavelet shrinkage algorithm. In order to realize real-time GPP, signals analysis, some key issues are discussed such as the realization of fast wavelet transformation, the selection of CPU chip and the optimization of data movement. Experimenial results show that the DSP based application not only basically meets the real-time requirement of GPP, signals analysis, but also assures the quality of the GPR signals analysis.
文摘Under the complex condition of nuclear power plant, all kinds of influence factors may cause distortion of on-line monitoring data. It is essential that on-line monitoring data should be de-noised in order to ensure the accuracy of diagnosis. Based on the research of wavelet analysis and threshold de-noising, a new threshold denoising method based on Mallat transform is proposed. This method adopts factor weighing method for threshold quantization. Through the specific case of nuclear power plant, it is verified that the algorithm is of validity and superiority.
文摘The detection of the low-altitude acoustic target is an important way to compensate for the weakness of radar.Removing the noise mixed in acoustic signal as much as possible to retain the useful information is a challenging task.Inspired by the wavelet threshold,the de-noising method for low-altitude battlefield acoustic signal based on threshold empirical mode decomposition(EMD-T)is proposed in this paper.Firstly,the noisy signal is decomposed by empirical mode decomposition(EMD)to get the intrinsic mode functions(IMFs).Then the IMFs,whose actual energy exceeds its estimated energy,are processed by the EMD threshold.Finally,the processed IMFs are summed to reconstruct the de-noised signal.To evaluate the performance of the proposed method,extensive simulations are performed using helicopter sound corrupted with four types of typical low-altitude ambient noise under different signal-to-noise ratio(SNR)input values.The performance is evaluated in terms of SNR,root mean square error(RMSE)and smoothness index(SI).The simulations results reveal that the proposed method de-noising method has the perspective of the highest SNR,smallest RMSE and SI in de-noising low-altitude ambient noise compared to other methods,including the wavelet transform(WT)and conventional EMD.
文摘目的:比较大强度间歇训练(High-intensity Interval Training,HIT)和中等强度持续训练(Moderate-intensity Continuous Training,MCT)对斜坡测试(Ramp)、中等强度及高强度持续运动中耗氧量动力学(OUK,Oxygen Uptake Kinetics)等参数的影响。方法:36名青年男性受试者分为高强度间歇训练组(HIT)、中等强度持续训练组(MCT,)和对照组(NOT),MCT和HIT两干预组分别进行6周、每周3次强度不同而训练量相同的运动干预;各组干预前(Pre)、中(Mid)、后(Post)分别进行Ramp力竭测试及中、高强度持续运动的OUK测试。结果:6周干预后,HIT与MCT两干预组VO_2max/kg(最大耗氧量)、VO_2-VAT(通气无氧阈耗氧量)、VO_2/kg-VAT(通气无氧阈耗氧量相对值)、Waat-VAT(通气无氧阈功率)均表现为干预后值高于干预前(P<0.05)、干预中值(P<0.01);3组受试者之间上述参数组间差异显著(P<0.05),但仅表现HIT、MCT组与NOT组之间差异显著,HIT与MCT两组之间差异不显著(P>0.05);A_(slop)(Delta效率)、A_(OUES)(耗氧效率坡度)组间效应不显著(P>0.05)。中等强度下OUK各参数仅有τ(Tau,OUK时间常数)值组间效应显著(F=3.652,P=0.04<0.05),HIT与MCT两干预组分别与NOT之间组间效应显著(HIT vs NOT,P=0.027<0.05;MCT vs NOT,P=0.027<0.05),但HIT、MCT两干预组Mid、Post阶段,组间差异不显著(P>0.05),各组各时间点TD值、A值组间差异不显著(P>0.05)。大强度运动时A1(A,耗氧幅度)值组间效应显著(F=4.439,P=0.011<0.05),除了MCT及HIT分别与NOT组组间差异显著外,HIT与MCT之间差异显著(P<0.05),6周后HIT组A1值显著高于同阶段MCT组(1 893.9±132.1vs 1 632.3±340.0,P<0.05);而对于观测值τ_1,3组受试者之间组间效应显著(F=9.083,P<0.01),MIT及HIT组和NOT组相比,τ_1显著降低,并且MIT和HIT组间差异显著(P<0.05);3周后HIT组τ_1值已经显著高于NOT组(Mid:42.5±3.8 vs 53.7±4.3,P<0.01),而MCT在6周后出现(Post:43.1±4.6 vs 53.4±6.0,P<0.01)。3周后HIT组A2值比NOT组显著减低(P<0.05),6周后Post值显著低于MCT组及NOT组同阶段值(P<0.01),而MCT组在各阶段与NOT组之间差异不显著(P>0.05)。τ_2虽有所升高,但并无显著意义(P>0.05)。结论:大强度间歇训练和中等强度持续训练均可提高VO_2max、VAT等心肺耐力评定参数,但两种训练模式对上述参数改善并无显著区别;两训练模式对中等强度下耗氧动力参数影响无显著区别,但大强度间歇训练在提高大强度运动过程中氧耗应答速率及减少耗氧量慢成分方面有着更明显的优势。
