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） perfo...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 liD 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 liD 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
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
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
In accordance with the application requirements of high definition(HD) video surveillance systems,a real-time 5/3 lifting wavelet HD-video de-noising system is proposed with frame rate conversion(FRC) based on a field...In accordance with the application requirements of high definition(HD) video surveillance systems,a real-time 5/3 lifting wavelet HD-video de-noising system is proposed with frame rate conversion(FRC) based on a field-programmable gate array(FPGA),which uses a 3-level pipeline paralleled 5/3 lifting wavelet transformation and reconstruction structure,as well as a fast BayesS hrink adaptive threshold filtering module.The proposed system demonstrates de-noising performance,while also balancing system resources and achieving real-time processing.The experiments show that the proposed system's maximum operating frequency(through logic synthesis and layout using Quartus 13.1 software) can reach 178 MHz,based on the Altera Company's Stratix III EP3SE80 series FPGA.The proposed system can also satisfy real-time de-noising requirements of 1920 × 1080 at60 fps HD-video sources,while also significantly improving the peak signal to noise rate of the denoising images.Compared with similar systems,the system has the advantages of high operating frequency,and the ability to support multiple source formats for real-time processing.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 liD 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 liD and ADT was evaluated in realistic IEEE 802.15.4a UWB channel models and the simulation results demonstrated our theoretical analysis.
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.
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.
基金Supported by the Spark Program of China(No.2013GA780007)Key Scientific Research Project of Guandong Agriculture Industry Business Polytechnic(No.xyzd1604)
文摘In accordance with the application requirements of high definition(HD) video surveillance systems,a real-time 5/3 lifting wavelet HD-video de-noising system is proposed with frame rate conversion(FRC) based on a field-programmable gate array(FPGA),which uses a 3-level pipeline paralleled 5/3 lifting wavelet transformation and reconstruction structure,as well as a fast BayesS hrink adaptive threshold filtering module.The proposed system demonstrates de-noising performance,while also balancing system resources and achieving real-time processing.The experiments show that the proposed system's maximum operating frequency(through logic synthesis and layout using Quartus 13.1 software) can reach 178 MHz,based on the Altera Company's Stratix III EP3SE80 series FPGA.The proposed system can also satisfy real-time de-noising requirements of 1920 × 1080 at60 fps HD-video sources,while also significantly improving the peak signal to noise rate of the denoising images.Compared with similar systems,the system has the advantages of high operating frequency,and the ability to support multiple source formats for real-time processing.
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.
