The earthquake size distribution is generally considered to obey the Gutenberg Richter (GR) law. We have introduced the concept of the b value spectrum based on the moment method to investigate the deviation of t...The earthquake size distribution is generally considered to obey the Gutenberg Richter (GR) law. We have introduced the concept of the b value spectrum based on the moment method to investigate the deviation of the actual magnitude distribution of earthquakes from this law. This enables us to describe characteristic features of the magnitude frequency distribution of earthquakes. We found also a simple relation between the η value and the b value spectrum. Analysis using this scheme showed that the actual size distributions of earthquakes have large variations from case to case and sometimes deviate considerably from the widely assumed the GR formula.展开更多
Based on the universal expression of wind wave spectra, four commonly used definitions of the spectrum width are re-examined. The results show that the non-dimensional spectrum width can measure the width of non-dimen...Based on the universal expression of wind wave spectra, four commonly used definitions of the spectrum width are re-examined. The results show that the non-dimensional spectrum width can measure the width of non-dimensional spectra but it does not reflect the developing state of the spectra. The dimensional spectrum width expresses the degree of concentration of wave energy of the spectrum in the process of wind wave growth. Tests show that the spectrum width presented by Wen et al. can objectively measure the degree of concentration of wave energy of the spectrum, reflect the state of wind wave growth, and provides a better result for practical application, The rules for definition of the spectrum width are discussed.展开更多
The method of the moment excitation in the studies of the structure-borne sound using a moment actuator is introduced. Some design considerations for the moment actuator are presented. A standard mechanical system is ...The method of the moment excitation in the studies of the structure-borne sound using a moment actuator is introduced. Some design considerations for the moment actuator are presented. A standard mechanical system is established to calibrate the performance of the moment actuator. The frequency and mechanical power performances of the actuator are discussed.展开更多
It has been analyzed the influence of the tectonic ambient shear stress value on response spectrum based on the previous theory. Based on the prediction equation BJF94 presented by the famous American researchers, CLB...It has been analyzed the influence of the tectonic ambient shear stress value on response spectrum based on the previous theory. Based on the prediction equation BJF94 presented by the famous American researchers, CLB20, a new prediction formula is proposed by us, where it is introduced the influence of tectonic ambient shear stress value on response spectrum. BJF94 is the prediction equation, which mainly depends on strong ground motion data from western USA, while the prediction equation SEA99 is based on the strong ground motion data from exten-sional region all over the world. Comparing these two prediction equations in detail, it is found that after BJF94′s prediction value lg(Y) minus 0.16 logarithmic units, the value is very close to SEA99′s one. This case demonstrates that lg(Y) in extensional region is smaller; the differences of prediction equation are mainly owe to the differences of tectonic ambient shear stress value. If the factor of tectonic ambient shear stress value is included into the pre-diction equation, and the magnitude is used seismic moment magnitude to express, which is universal used around the world, and the distance is used the distance of fault project, which commonly used by many people, then re-gional differences of prediction equation will become much less, even vanish, and it can be constructed the uni-versal prediction equation proper to all over the world. The error in the earthquake-resistant design in China will be small if we directly use the results of response spectrum of USA (e.g. BJF94 or SEA99).展开更多
The existing recognition algorithms of space-time block code(STBC)for multi-antenna(MA)orthogonal frequencydivision multiplexing(OFDM)systems use feature extraction and hypothesis testing to identify the signal types ...The existing recognition algorithms of space-time block code(STBC)for multi-antenna(MA)orthogonal frequencydivision multiplexing(OFDM)systems use feature extraction and hypothesis testing to identify the signal types in a complex communication environment.However,owing to the restrictions on the prior information and channel conditions,these existing algorithms cannot perform well under strong interference and noncooperative communication conditions.To overcome these defects,this study introduces deep learning into the STBCOFDM signal recognition field and proposes a recognition method based on the fourth-order lag moment spectrum(FOLMS)and attention-guided multi-scale dilated convolution network(AMDCNet).The fourth-order lag moment vectors of the received signals are calculated,and vectors are stitched to form two-dimensional FOLMS,which is used as the input of the deep learning-based model.Then,the multi-scale dilated convolution is used to extract the details of images at different scales,and a convolutional block attention module(CBAM)is introduced to construct the attention-guided multi-scale dilated convolution module(AMDCM)to make the network be more focused on the target area and obtian the multi-scale guided features.Finally,the concatenate fusion,residual block and fully-connected layers are applied to acquire the STBC-OFDM signal types.Simulation experiments show that the average recognition probability of the proposed method at−12 dB is higher than 98%.Compared with the existing algorithms,the recognition performance of the proposed method is significantly improved and has good adaptability to environments with strong disturbances.In addition,the proposed deep learning-based model can directly identify the pre-processed FOLMS samples without a priori information on channel and noise,which is more suitable for non-cooperative communication systems than the existing algorithms.展开更多
Compared with the histogram of Discrete Cosine Transform (DCT) coefficients before the Direct Sequence Spread Spectrum (DSSS) embedding, the peak value of the histogram after the embedding decreases and expands toward...Compared with the histogram of Discrete Cosine Transform (DCT) coefficients before the Direct Sequence Spread Spectrum (DSSS) embedding, the peak value of the histogram after the embedding decreases and expands toward the border. Based on the property, an audio steganalysis of DSSS based on statistical moments of histogram is proposed. The statistical moments of the histogram in DCT domain and its frequency domain and the statistical moments of the histogram of the wavelet coefficients of every level in frequency domain are calculated as the features of classification. Support Vector Machine (SVM) is exploited as the classifier. Experimental results show that the proposed technique is effective on the DSSS embedding in DCT domain using different embedding length, and the average detection rate is 91.75%.展开更多
针对基于特征值的谱感知算法在脉冲噪声的环境下感知性能不佳的问题,分析矩阵全部的特征值,引入矩阵特征值的几何均值,提出了基于分数低阶协方差矩阵的最大特征值与特征值几何均值之差(difference between maximum eigenvalue and geome...针对基于特征值的谱感知算法在脉冲噪声的环境下感知性能不佳的问题,分析矩阵全部的特征值,引入矩阵特征值的几何均值,提出了基于分数低阶协方差矩阵的最大特征值与特征值几何均值之差(difference between maximum eigenvalue and geometric mean of eigenvalue,DMGM)的频谱感知算法。选择了Alpha稳定分布噪声模拟脉冲噪声环境,理论分析与仿真实验结果表明,在不增加算法复杂度的前提下,DMGM算法与其他算法相比,更适用于脉冲噪声环境,在低信噪比条件下具有更好的感知性能。展开更多
结合局域均值分解(Local mean decomposition,LMD)方法和Wigner高阶矩谱,提出一种基于局域均值分解的Wigner高阶矩谱的机械故障诊断方法,该方法保留了LMD和Wigner高阶矩谱的所有优良性能,有效地抑制了Wigner高阶矩谱的交叉项的干扰。仿...结合局域均值分解(Local mean decomposition,LMD)方法和Wigner高阶矩谱,提出一种基于局域均值分解的Wigner高阶矩谱的机械故障诊断方法,该方法保留了LMD和Wigner高阶矩谱的所有优良性能,有效地抑制了Wigner高阶矩谱的交叉项的干扰。仿真结果表明,提出的方法优于直接Wigner高阶矩谱和Choi-Williams核滤波后的Wigner高阶矩谱。最后,将该方法应用到轴承故障诊断中,实验结果进一步验证了该方法的的有效性。展开更多
文摘The earthquake size distribution is generally considered to obey the Gutenberg Richter (GR) law. We have introduced the concept of the b value spectrum based on the moment method to investigate the deviation of the actual magnitude distribution of earthquakes from this law. This enables us to describe characteristic features of the magnitude frequency distribution of earthquakes. We found also a simple relation between the η value and the b value spectrum. Analysis using this scheme showed that the actual size distributions of earthquakes have large variations from case to case and sometimes deviate considerably from the widely assumed the GR formula.
基金This work was financially supported by the National Science Foundation of China(Grant No.49776282)
文摘Based on the universal expression of wind wave spectra, four commonly used definitions of the spectrum width are re-examined. The results show that the non-dimensional spectrum width can measure the width of non-dimensional spectra but it does not reflect the developing state of the spectra. The dimensional spectrum width expresses the degree of concentration of wave energy of the spectrum in the process of wind wave growth. Tests show that the spectrum width presented by Wen et al. can objectively measure the degree of concentration of wave energy of the spectrum, reflect the state of wind wave growth, and provides a better result for practical application, The rules for definition of the spectrum width are discussed.
文摘The method of the moment excitation in the studies of the structure-borne sound using a moment actuator is introduced. Some design considerations for the moment actuator are presented. A standard mechanical system is established to calibrate the performance of the moment actuator. The frequency and mechanical power performances of the actuator are discussed.
基金National Natural Science Foundation of China (49874010)
文摘It has been analyzed the influence of the tectonic ambient shear stress value on response spectrum based on the previous theory. Based on the prediction equation BJF94 presented by the famous American researchers, CLB20, a new prediction formula is proposed by us, where it is introduced the influence of tectonic ambient shear stress value on response spectrum. BJF94 is the prediction equation, which mainly depends on strong ground motion data from western USA, while the prediction equation SEA99 is based on the strong ground motion data from exten-sional region all over the world. Comparing these two prediction equations in detail, it is found that after BJF94′s prediction value lg(Y) minus 0.16 logarithmic units, the value is very close to SEA99′s one. This case demonstrates that lg(Y) in extensional region is smaller; the differences of prediction equation are mainly owe to the differences of tectonic ambient shear stress value. If the factor of tectonic ambient shear stress value is included into the pre-diction equation, and the magnitude is used seismic moment magnitude to express, which is universal used around the world, and the distance is used the distance of fault project, which commonly used by many people, then re-gional differences of prediction equation will become much less, even vanish, and it can be constructed the uni-versal prediction equation proper to all over the world. The error in the earthquake-resistant design in China will be small if we directly use the results of response spectrum of USA (e.g. BJF94 or SEA99).
基金supported by the National Natural Science Foundation of China(91538201)the Taishan Scholar Foundation of China(ts201511020).
文摘The existing recognition algorithms of space-time block code(STBC)for multi-antenna(MA)orthogonal frequencydivision multiplexing(OFDM)systems use feature extraction and hypothesis testing to identify the signal types in a complex communication environment.However,owing to the restrictions on the prior information and channel conditions,these existing algorithms cannot perform well under strong interference and noncooperative communication conditions.To overcome these defects,this study introduces deep learning into the STBCOFDM signal recognition field and proposes a recognition method based on the fourth-order lag moment spectrum(FOLMS)and attention-guided multi-scale dilated convolution network(AMDCNet).The fourth-order lag moment vectors of the received signals are calculated,and vectors are stitched to form two-dimensional FOLMS,which is used as the input of the deep learning-based model.Then,the multi-scale dilated convolution is used to extract the details of images at different scales,and a convolutional block attention module(CBAM)is introduced to construct the attention-guided multi-scale dilated convolution module(AMDCM)to make the network be more focused on the target area and obtian the multi-scale guided features.Finally,the concatenate fusion,residual block and fully-connected layers are applied to acquire the STBC-OFDM signal types.Simulation experiments show that the average recognition probability of the proposed method at−12 dB is higher than 98%.Compared with the existing algorithms,the recognition performance of the proposed method is significantly improved and has good adaptability to environments with strong disturbances.In addition,the proposed deep learning-based model can directly identify the pre-processed FOLMS samples without a priori information on channel and noise,which is more suitable for non-cooperative communication systems than the existing algorithms.
基金Supported by the National Natural Science Foundation of China (No.60772032)
文摘Compared with the histogram of Discrete Cosine Transform (DCT) coefficients before the Direct Sequence Spread Spectrum (DSSS) embedding, the peak value of the histogram after the embedding decreases and expands toward the border. Based on the property, an audio steganalysis of DSSS based on statistical moments of histogram is proposed. The statistical moments of the histogram in DCT domain and its frequency domain and the statistical moments of the histogram of the wavelet coefficients of every level in frequency domain are calculated as the features of classification. Support Vector Machine (SVM) is exploited as the classifier. Experimental results show that the proposed technique is effective on the DSSS embedding in DCT domain using different embedding length, and the average detection rate is 91.75%.
文摘针对基于特征值的谱感知算法在脉冲噪声的环境下感知性能不佳的问题,分析矩阵全部的特征值,引入矩阵特征值的几何均值,提出了基于分数低阶协方差矩阵的最大特征值与特征值几何均值之差(difference between maximum eigenvalue and geometric mean of eigenvalue,DMGM)的频谱感知算法。选择了Alpha稳定分布噪声模拟脉冲噪声环境,理论分析与仿真实验结果表明,在不增加算法复杂度的前提下,DMGM算法与其他算法相比,更适用于脉冲噪声环境,在低信噪比条件下具有更好的感知性能。
文摘结合局域均值分解(Local mean decomposition,LMD)方法和Wigner高阶矩谱,提出一种基于局域均值分解的Wigner高阶矩谱的机械故障诊断方法,该方法保留了LMD和Wigner高阶矩谱的所有优良性能,有效地抑制了Wigner高阶矩谱的交叉项的干扰。仿真结果表明,提出的方法优于直接Wigner高阶矩谱和Choi-Williams核滤波后的Wigner高阶矩谱。最后,将该方法应用到轴承故障诊断中,实验结果进一步验证了该方法的的有效性。
