Seismic energy decays while propagating subsurface, which may reduce the resolution of seismic data. This paper studies the method of seismic energy dispersion compensation which provides the basic principles for mult...Seismic energy decays while propagating subsurface, which may reduce the resolution of seismic data. This paper studies the method of seismic energy dispersion compensation which provides the basic principles for multi-scale morphology and the spectrum simulation method. These methods are applied in seismic energy compensation. First of all, the seismic data is decomposed into multiple scales and the effective frequency bandwidth is selectively broadened for some scales by using a spectrum simulation method. In this process, according to the amplitude spectrum of each scale, the best simulation range is selected to simulate the middle and low frequency components to ensure the authenticity of the simulation curve which is calculated by the median method, and the high frequency component is broadened. Finally, these scales are reconstructed with reasonable coefficients, and the compensated seismic data can be obtained. Examples are shown to illustrate the feasibility of the energy compensation method.展开更多
In high intensity focused ultrasound(HIFU)treatment,it is crucial to accurately identify denatured and normal biological tissues.In this paper,a novel method based on compressed sensing(CS)and refined composite multi-...In high intensity focused ultrasound(HIFU)treatment,it is crucial to accurately identify denatured and normal biological tissues.In this paper,a novel method based on compressed sensing(CS)and refined composite multi-scale fuzzy entropy(RCMFE)is proposed.First,CS is used to denoise the HIFU echo signals.Then the multi-scale fuzzy entropy(MFE)and RCMFE of the denoised HIFU echo signals are calculated.This study analyzed 90 cases of HIFU echo signals,including 45 cases in normal status and 45 cases in denatured status,and the results show that although both MFE and RCMFE can be used to identify denatured tissues,the intra-class distance of RCMFE on each scale factor is smaller than MFE,and the inter-class distance is larger than MFE.Compared with MFE,RCMFE can calculate the complexity of the signal more accurately and improve the stability,compactness,and separability.When RCMFE is selected as the characteristic parameter,the RCMFE difference between denatured and normal biological tissues is more evident than that of MFE,which helps doctors evaluate the treatment effect more accurately.When the scale factor is selected as 16,the best distinguishing effect can be obtained.展开更多
Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of ...Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields.Reverse dispersion entropy(RDE)proposed by us recently,as a nonlinear dynamic analysis method,has the advantages of fast computing speed and strong anti-noise ability,which is more suitable for measuring the complexity of signal than traditional permutation entropy(PE)and dispersion entropy(DE).Empirical wavelet transform(EWT),based on the theory of wavelet analysis,can decompose a complex non-stationary signal into a number of empirical wavelet functions(EWFs)with compact support set spectrum,which has better decomposition performance than empirical mode decomposition(EMD)and its improved algorithms.Considering the advantages of RDE and EWT,on the one hand,we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy;on the other hand,we use RDE as the features of EWFs to improve the signal separability and stability.Finally,we propose a novel signal feature extraction technology based on EWT and RDE in this paper.Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals.Moreover,it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.展开更多
We extend the complexity entropy causality plane(CECP) to propose a multi-scale complexity entropy causality plane(MS-CECP) and further use the proposed method to discriminate the deterministic characteristics of ...We extend the complexity entropy causality plane(CECP) to propose a multi-scale complexity entropy causality plane(MS-CECP) and further use the proposed method to discriminate the deterministic characteristics of different oil-in-water flows. We first take several typical time series for example to investigate the characteristic of the MS-CECP and find that the MS-CECP not only describes the continuous loss of dynamical structure with the increase of scale, but also reflects the determinacy of the system. Then we calculate the MS-CECP for the conductance fluctuating signals measured from oil–water two-phase flow loop test facility. The results indicate that the MS-CECP could be an intrinsic measure for indicating oil-in-water two-phase flow structures.展开更多
There is much interest in resolving the quantum corrections to Bekenstein-Hawking entropy with a largelength scale limit.The leading correction term is given by the logarithm of black hole area with a model-dependentc...There is much interest in resolving the quantum corrections to Bekenstein-Hawking entropy with a largelength scale limit.The leading correction term is given by the logarithm of black hole area with a model-dependentcoefficient.Recently the research for quantum gravity implies the emergence of a modification of the energy-momentumdispersion relation (MDR),which plays an important role in the modified black hole thermodynamics.In this paper,weinvestigate the quantum corrections to Bekenstein-Hawking entropy in four-dimensional Schwarzschild black hole andReissner Nordstr(o|¨)m black hole respectively based on MDR.展开更多
In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,ex...In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,expensive equipment,low accuracy,and difficulty in real-time monitoring.The proposed system is based on Commodity WiFi and is easy to deploy.Leveraging WiFi CSI data,this paper proposes a feature extraction method based on multi-scale and multi-channel entropy.The feasibility and stability of the system are validated through experiments in both Line-Of-Sight(LOS)and Non-Line-Of-Sight(NLOS)scenarios,where ten types of wheat moisture content are tested using multi-class Support Vector Machine(SVM).Compared with the Wi-Wheat system proposed in our prior work,Wi-Wheatþhas higher efficiency,requiring only a simple training process,and can sense more wheat moisture content levels.展开更多
Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method ...Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy features.Then,the fuzzy BLS takes the above entropy features as input to complete model training.Fuzzy BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational speed.Experimental results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.展开更多
We analyze correlations and patterns of oxidative activity of 3D DNA at DNA fluorescence in complete sets of chromosomes in neutrophils of peripheral blood. Fluorescence of DNA is registered by method of flow cytometr...We analyze correlations and patterns of oxidative activity of 3D DNA at DNA fluorescence in complete sets of chromosomes in neutrophils of peripheral blood. Fluorescence of DNA is registered by method of flow cytometry with nanometer spatial resolution. Experimental data present fluorescence of many ten thousands of cells, from different parts of body in each population, in various blood samples. Data is presented in histograms as frequency distributions of flashes in the dependence on their intensity. Normalized frequency distribution of information in these histograms is used as probabilistic measure for definition of Shannon entropy. Data analysis shows that for this measure of Shannon entropy common sum of entropy, i.e. total entropy E, for any histogram is invariant and has identical trends of changes all values of E (r) = lnr at reduction of rank r of histogram. This invariance reflects informational homeostasis of chromosomes activity inside cells in multi-scale networks of entropy, for varied ranks r. Shannon entropy in multi-scale DNA networks has much more dense packing of correlations than in “small world” networks. As the rule, networks of entropy differ by the mix of normal D 2 and abnormal D > 2 fractal dimensions for varied ranks r, the new types of fractal patterns and hinges for various topology (fractal dimension) at different states of health. We show that all distributions of information entropy are divided on three classes, which associated in diagnostics with a good health or dominants of autoimmune or inflammatory diseases. This classification based on switching of stability at transcritical bifurcation in homeostasis regulation. We defined many ways for homeostasis regulation, coincidences and switching patterns in branching sequences, the averages of Hölder for deviations of entropy from homeostasis at different states of health, with various saturation levels the noises of entropy at activity of all chromosomes in support regulation of homeostasis.展开更多
文摘Seismic energy decays while propagating subsurface, which may reduce the resolution of seismic data. This paper studies the method of seismic energy dispersion compensation which provides the basic principles for multi-scale morphology and the spectrum simulation method. These methods are applied in seismic energy compensation. First of all, the seismic data is decomposed into multiple scales and the effective frequency bandwidth is selectively broadened for some scales by using a spectrum simulation method. In this process, according to the amplitude spectrum of each scale, the best simulation range is selected to simulate the middle and low frequency components to ensure the authenticity of the simulation curve which is calculated by the median method, and the high frequency component is broadened. Finally, these scales are reconstructed with reasonable coefficients, and the compensated seismic data can be obtained. Examples are shown to illustrate the feasibility of the energy compensation method.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11774088 and 11474090)。
文摘In high intensity focused ultrasound(HIFU)treatment,it is crucial to accurately identify denatured and normal biological tissues.In this paper,a novel method based on compressed sensing(CS)and refined composite multi-scale fuzzy entropy(RCMFE)is proposed.First,CS is used to denoise the HIFU echo signals.Then the multi-scale fuzzy entropy(MFE)and RCMFE of the denoised HIFU echo signals are calculated.This study analyzed 90 cases of HIFU echo signals,including 45 cases in normal status and 45 cases in denatured status,and the results show that although both MFE and RCMFE can be used to identify denatured tissues,the intra-class distance of RCMFE on each scale factor is smaller than MFE,and the inter-class distance is larger than MFE.Compared with MFE,RCMFE can calculate the complexity of the signal more accurately and improve the stability,compactness,and separability.When RCMFE is selected as the characteristic parameter,the RCMFE difference between denatured and normal biological tissues is more evident than that of MFE,which helps doctors evaluate the treatment effect more accurately.When the scale factor is selected as 16,the best distinguishing effect can be obtained.
基金the supported by National Natural Science Foundation of China(No.61871318 and 11574250)Scientific Research Plan Projects of Shaanxi Education Department(No.19JK0568).
文摘Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields.Reverse dispersion entropy(RDE)proposed by us recently,as a nonlinear dynamic analysis method,has the advantages of fast computing speed and strong anti-noise ability,which is more suitable for measuring the complexity of signal than traditional permutation entropy(PE)and dispersion entropy(DE).Empirical wavelet transform(EWT),based on the theory of wavelet analysis,can decompose a complex non-stationary signal into a number of empirical wavelet functions(EWFs)with compact support set spectrum,which has better decomposition performance than empirical mode decomposition(EMD)and its improved algorithms.Considering the advantages of RDE and EWT,on the one hand,we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy;on the other hand,we use RDE as the features of EWFs to improve the signal separability and stability.Finally,we propose a novel signal feature extraction technology based on EWT and RDE in this paper.Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals.Moreover,it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.41174109 and 61104148)the National Science and Technology Major Project of China(Grant No.2011ZX05020-006)the Zhejiang Key Discipline of Instrument Science and Technology,China(Grant No.JL130106)
文摘We extend the complexity entropy causality plane(CECP) to propose a multi-scale complexity entropy causality plane(MS-CECP) and further use the proposed method to discriminate the deterministic characteristics of different oil-in-water flows. We first take several typical time series for example to investigate the characteristic of the MS-CECP and find that the MS-CECP not only describes the continuous loss of dynamical structure with the increase of scale, but also reflects the determinacy of the system. Then we calculate the MS-CECP for the conductance fluctuating signals measured from oil–water two-phase flow loop test facility. The results indicate that the MS-CECP could be an intrinsic measure for indicating oil-in-water two-phase flow structures.
基金Supported by the National Natural Science Foundation of China under Grant No.10573004
文摘There is much interest in resolving the quantum corrections to Bekenstein-Hawking entropy with a largelength scale limit.The leading correction term is given by the logarithm of black hole area with a model-dependentcoefficient.Recently the research for quantum gravity implies the emergence of a modification of the energy-momentumdispersion relation (MDR),which plays an important role in the modified black hole thermodynamics.In this paper,weinvestigate the quantum corrections to Bekenstein-Hawking entropy in four-dimensional Schwarzschild black hole andReissner Nordstr(o|¨)m black hole respectively based on MDR.
基金supported in part by the Program for Science&Technology Innovation Talents in Universities of Henan Province(19HASTIT027)National Natural Science Foundation of China(62172141)+4 种基金Zhengzhou Major Scientific and Technological Innovation Project(2019CXZX0086)Youth Innovative Talents Cultivation Fund Project of Kaifeng University in 2020(KDQN-2020-GK002)the National Key Research and Development Program of China(2017YFD0401001)the NSFC(61741107),the NSF(CNS-2105416)by the Wireless Engineering Research and Education Center at Auburn University.
文摘In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,expensive equipment,low accuracy,and difficulty in real-time monitoring.The proposed system is based on Commodity WiFi and is easy to deploy.Leveraging WiFi CSI data,this paper proposes a feature extraction method based on multi-scale and multi-channel entropy.The feasibility and stability of the system are validated through experiments in both Line-Of-Sight(LOS)and Non-Line-Of-Sight(NLOS)scenarios,where ten types of wheat moisture content are tested using multi-class Support Vector Machine(SVM).Compared with the Wi-Wheat system proposed in our prior work,Wi-Wheatþhas higher efficiency,requiring only a simple training process,and can sense more wheat moisture content levels.
基金supported in part by the Fundamental Research Funds for the Central Universities(Grant No.2021RC271)NSFC(Grants No.62120106011,52172323 and U22A2046).
文摘Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy features.Then,the fuzzy BLS takes the above entropy features as input to complete model training.Fuzzy BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational speed.Experimental results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.
文摘We analyze correlations and patterns of oxidative activity of 3D DNA at DNA fluorescence in complete sets of chromosomes in neutrophils of peripheral blood. Fluorescence of DNA is registered by method of flow cytometry with nanometer spatial resolution. Experimental data present fluorescence of many ten thousands of cells, from different parts of body in each population, in various blood samples. Data is presented in histograms as frequency distributions of flashes in the dependence on their intensity. Normalized frequency distribution of information in these histograms is used as probabilistic measure for definition of Shannon entropy. Data analysis shows that for this measure of Shannon entropy common sum of entropy, i.e. total entropy E, for any histogram is invariant and has identical trends of changes all values of E (r) = lnr at reduction of rank r of histogram. This invariance reflects informational homeostasis of chromosomes activity inside cells in multi-scale networks of entropy, for varied ranks r. Shannon entropy in multi-scale DNA networks has much more dense packing of correlations than in “small world” networks. As the rule, networks of entropy differ by the mix of normal D 2 and abnormal D > 2 fractal dimensions for varied ranks r, the new types of fractal patterns and hinges for various topology (fractal dimension) at different states of health. We show that all distributions of information entropy are divided on three classes, which associated in diagnostics with a good health or dominants of autoimmune or inflammatory diseases. This classification based on switching of stability at transcritical bifurcation in homeostasis regulation. We defined many ways for homeostasis regulation, coincidences and switching patterns in branching sequences, the averages of Hölder for deviations of entropy from homeostasis at different states of health, with various saturation levels the noises of entropy at activity of all chromosomes in support regulation of homeostasis.