Code acquisition is the kernel operation for signal synchronization in the spread-spectrum receiver.To reduce the computational complexity and latency of code acquisition,this paper proposes an efficient scheme employ...Code acquisition is the kernel operation for signal synchronization in the spread-spectrum receiver.To reduce the computational complexity and latency of code acquisition,this paper proposes an efficient scheme employing sparse Fourier transform(SFT)and the relevant hardware architecture for field programmable gate array(FPGA)and application-specific integrated circuit(ASIC)implementation.Efforts are made at both the algorithmic level and the implementation level to enable merged searching of code phase and Doppler frequency without incurring massive hardware expenditure.Compared with the existing code acquisition approaches,it is shown from theoretical analysis and experimental results that the proposed design can shorten processing latency and reduce hardware complexity without degrading the acquisition probability.展开更多
To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform （STFT） is brought forward. ...To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform （STFT） is brought forward. First the physical essence of aliasing that occurs is analyzed; second the interpolation algorithm model is setup based on the Hamming window; then the fast implementation of the algorithm using the Newton iteration method is given. Using the numerical simulation the feasibility of algorithm is validated. Finally, the electrical circuit experiment shows the practicality of the algorithm in the electrical engineering.展开更多
Traditionally,beamforming using fractional Fourier transform（FrFT） involves a trial-and-error based FrFT order selection which is impractical.A new numerical order selection scheme is presented based on fractional p...Traditionally,beamforming using fractional Fourier transform（FrFT） involves a trial-and-error based FrFT order selection which is impractical.A new numerical order selection scheme is presented based on fractional power spectra（FrFT moment） of the linear chirp signal.This method can adaptively determine the optimum FrFT order by maximizing the second-order central FrFT moment.This makes the desired chirp signal substantially concentrated whereas the noise is rejected considerably.This improves the mean square error minimization beamformer by reducing effectively the signal-noise cross terms due to the finite data length de-correlation operation.Simulation results show that the new method works well under a wide range of signal to noise ratio and signal to interference ratio.展开更多
Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributio...Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.展开更多
In low earth orbit (LEO) satellite or missile communication scenarios, signals may experience extremely large Doppler shifts and have short visual time. Thus, direct sequence spread spectrum (DSSS) systems should be a...In low earth orbit (LEO) satellite or missile communication scenarios, signals may experience extremely large Doppler shifts and have short visual time. Thus, direct sequence spread spectrum (DSSS) systems should be able to achieve acquisition in a very short time in spite of large Doppler frequencies. However, the traditional methods cannot solve it well. This work describes a new method that uses a differential decoding technique for Doppler mitigation and a batch process of FFT (fast Fourier transform) and IFFT (invert FFT) for the purpose of parallel code phase search by frequency domain correlation. After the code phase is estimated, another FFT process is carried out to search the Doppler frequency. Since both code phase and Doppler frequency domains are searched in parallel, this architecture can provide acquisition fifty times faster than conventional FFT methods. The performance in terms of the probability of detection and false alarm are also analyzed and simulated, showing that a signal-to-noise ratio (SNR) loss of 3 dB is introduced by the differential decoding. The proposed method is an efficient way to shorten the acquisition time with slightly hardware increasing.展开更多
Background:The majority of attenuated total reflection Fourier transform infrared(ATR FT-IR)investigations of cotton are focused on the fiber tissue for biological mechanisms and understanding of fiber development and...Background:The majority of attenuated total reflection Fourier transform infrared(ATR FT-IR)investigations of cotton are focused on the fiber tissue for biological mechanisms and understanding of fiber development and maturity,but rarely on other cotton biomass comp on ents.This work examined in detail the ATR FT-IR spectral features of various cott on tissues/organs at reproductive and maturation stages,an a lyzed and discussed their biological implications.Results:The ATR FT-IR spectra of these tissues/organs were an a lyzed and compared with the focus on the lower wavenumber fingerprinting range.Six outstanding FT-IR bands at 1730,1620,1525,1235,1050 and 895 cm^(-1) represented the major C=O stretching,protein Amide I,Amide II,the O-H/N-H deformation,the total C-O-C stretching and the β-glycosidic linkage in celluloses,respectively,and impacted differently between these organs with the two growth stages.Furthermore,the band intensity at 1620,1525,1235,and 1050 cm^(-1) were exclusively and significantly correlated to the levels of protein(Amide I bond),protein(Amide II bond),cellulose,and hemicellulose,respectively,whereas the band at 1730 cm^(-1) was negatively correlated with ash content.Conclusions:The resulting observations indicated the capability of ATR FT-IR spectroscopy for monitoring changes,transportation,and accumulation of the major chemical components in these tissues over the cotton growth period.In other words,this spectral technology could be an effective tool for physiological,biochemical,and morphological research related to cotton biology and development.展开更多
Identification of plant-pathogenic fungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the micro-morphological characters observed.The present investig...Identification of plant-pathogenic fungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the micro-morphological characters observed.The present investigation aimed to create a simple but sophisticated method for the identification of plant-pathogenic fungi by Fourier transform infrared(FTIR)spectroscopy.In this study,FTIR-attenuated total reflectance(ATR)spectroscopy was used in combination with chemometric analysis for identification of important pathogenic fungi of horticultural plants.Mixtures of mycelia and spores from 27fungal strains belonging to nine different families were collected from liquid PD or solid PDA media cultures and subjected to FTIR-ATR spectroscopy measurements.The FTIR-ATR spectra ranging from 4 000to 400cm-1 were obtained.To classify the FTIRATR spectra,cluster analysis was compared with canonical vitiate analysis(CVA)in the spectral regions of3 050~2 800and 1 800~900cm-1.Results showed that the identification accuracies achieved 97.53%and99.18%for the cluster analysis and CVA analysis,respectively,demonstrating the high potential of this technique for fungal strain identification.展开更多
The mismatch between echo and replica caused by underwater moving target(UMT)'s radial velocity degrades the detection performance of the matched filter(MF)for the linear frequency modulation(LFM)signal.By using t...The mismatch between echo and replica caused by underwater moving target(UMT)'s radial velocity degrades the detection performance of the matched filter(MF)for the linear frequency modulation(LFM)signal.By using the focusing property of fractional Fourier transform(FRFT)to that signal,a detection algorithm for UMT's LFM echo based on the discrete fractional Fourier transform(DFRFT)is proposed.This algorithm is less affected by the target's radial velocity compared with the other MF detection algorithm utilizing zero radial velocity replica(ZRVR),and the mathematical relation between the output peak positions of these two algorithms exists in the case of existence of target echo.The algorithm can also estimate the target distance by using this relation.The simulation and experiment show that this algorithm'sdetection performance is better than or equivalent to that of the other MF algorithm utilizing ZRVR for the LFM echo of UMT with unknown radial velocity under reverberation noise background.展开更多
Fractional Fourier transform(FRFT)is a linear transform generalizing Fourier transform(FT)that plays an important role in the field of signal processing and analysis.FRFT contains an adjustable parameterα,which it ro...Fractional Fourier transform(FRFT)is a linear transform generalizing Fourier transform(FT)that plays an important role in the field of signal processing and analysis.FRFT contains an adjustable parameterα,which it rotates the signal in the time frequency plane and represents the signal in an intermediate domain between time and frequency.FRFT provides a measure about the angular distribution of signal’s energy in time frequency plane.FT is a special case of FRFT when angleαis equal toπ/2.This paper presents mathematical model for obtaining FRFT of PC6 window function.The different parameters of this window function are also obtained with the help of simulation results.A comparison of window function parameters is presented using FT and FRFT.Also comparison of this window function with Hanning window function is presented in terms of Side Lobe Fall off Rate(SLFOR).For different values of FRFT order,PC6 window function shows variation in different parameters.Thus by changing the FRFT order,the minimum stop band attenuation of the resulting window function can be controlled.展开更多
针对现有深度学习算法在壁画修复时,存在全局语义一致性约束不足及局部特征提取不充分,导致修复后的壁画易出现边界效应和细节模糊等问题,提出一种双向自回归Transformer与快速傅里叶卷积增强的壁画修复方法.首先,设计基于Transformer...针对现有深度学习算法在壁画修复时,存在全局语义一致性约束不足及局部特征提取不充分,导致修复后的壁画易出现边界效应和细节模糊等问题,提出一种双向自回归Transformer与快速傅里叶卷积增强的壁画修复方法.首先,设计基于Transformer结构的全局语义特征修复模块,利用双向自回归机制与掩码语言模型(masked language modeling,MLM),提出改进的多头注意力全局语义壁画修复模块,提高对全局语义特征的修复能力.然后,构建了由门控卷积和残差模块组成的全局语义增强模块,增强全局语义特征一致性约束.最后,设计局部细节修复模块,采用大核注意力机制(large kernel attention,LKA)与快速傅里叶卷积提高细节特征的捕获能力,同时减少局部细节信息的丢失,提升修复壁画局部和整体特征的一致性.通过对敦煌壁画数字化修复实验,结果表明,所提算法修复性能更优,客观评价指标均优于比较算法.展开更多
Fault detection of an induction motor was carried out using the information of the stator current. After synchronizing the actual data, Fourier and wavelet transformations were adopted in order to obtain the sideband ...Fault detection of an induction motor was carried out using the information of the stator current. After synchronizing the actual data, Fourier and wavelet transformations were adopted in order to obtain the sideband or detail value characteristics under healthy and various faulty operating conditions. The most reliable phase current among the three phase currents was selected using an approach that employs the fuzzy entropy measure. Data were trained with a neural network system, and the fault detection algorithm was verified using the unknown data. Results of the proposed approach based on Fourier and wavelet transformations indicate that the faults can be properly classified into six categories. The training error is 5.3×10-7, and the average test error is 0.103.展开更多
基金supported by the National Natural Science Foundation of China(61801503).
文摘Code acquisition is the kernel operation for signal synchronization in the spread-spectrum receiver.To reduce the computational complexity and latency of code acquisition,this paper proposes an efficient scheme employing sparse Fourier transform(SFT)and the relevant hardware architecture for field programmable gate array(FPGA)and application-specific integrated circuit(ASIC)implementation.Efforts are made at both the algorithmic level and the implementation level to enable merged searching of code phase and Doppler frequency without incurring massive hardware expenditure.Compared with the existing code acquisition approaches,it is shown from theoretical analysis and experimental results that the proposed design can shorten processing latency and reduce hardware complexity without degrading the acquisition probability.
基金the National Natural Science Foundation of China (90407007 60372001).
文摘To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform （STFT） is brought forward. First the physical essence of aliasing that occurs is analyzed; second the interpolation algorithm model is setup based on the Hamming window; then the fast implementation of the algorithm using the Newton iteration method is given. Using the numerical simulation the feasibility of algorithm is validated. Finally, the electrical circuit experiment shows the practicality of the algorithm in the electrical engineering.
基金supported by the National Natural Science Foundation of China(61571088)the State High-Tech Development Plan(the 863 Program)(2015AA7031093B2015AA8098088B)
基金supported by the National Natural Science Foundation of China (606720846060203760736006)
文摘Traditionally,beamforming using fractional Fourier transform（FrFT） involves a trial-and-error based FrFT order selection which is impractical.A new numerical order selection scheme is presented based on fractional power spectra（FrFT moment） of the linear chirp signal.This method can adaptively determine the optimum FrFT order by maximizing the second-order central FrFT moment.This makes the desired chirp signal substantially concentrated whereas the noise is rejected considerably.This improves the mean square error minimization beamformer by reducing effectively the signal-noise cross terms due to the finite data length de-correlation operation.Simulation results show that the new method works well under a wide range of signal to noise ratio and signal to interference ratio.
基金This work was supported by the National Natural Science Foundation of China(91538201)the Taishan Scholar Project of Shandong Province(ts201511020)the project supported by Chinese National Key Laboratory of Science and Technology on Information System Security(6142111190404).
文摘Recent advances in electronics have increased the complexity of radar signal modulation.The quasi-linear frequency modulation(quasi-LFM)radar waveforms(LFM,Frank code,P1−P4 code)have similar time-frequency distributions,and it is difficult to identify such signals using traditional time-frequency analysis methods.To solve this problem,this paper proposes an algorithm for automatic recognition of quasi-LFM radar waveforms based on fractional Fourier transform and time-frequency analysis.First of all,fractional Fourier transform and the Wigner-Ville distribution(WVD)are used to determine the number of main ridgelines and the tilt angle of the target component in WVD.Next,the standard deviation of the target component's width in the signal's WVD is calculated.Finally,an assembled classifier using neural network is built to recognize different waveforms by automatically combining the three features.Simulation results show that the overall recognition rate of the proposed algorithm reaches 94.17%under 0 dB.When the training data set and the test data set are mixed with noise,the recognition rate reaches 89.93%.The best recognition accuracy is achieved when the size of the training set is taken as 400.The algorithm complexity can meet the requirements of real-time recognition.
基金Project(60904090) supported by the National Natural Science Foundation of China
文摘In low earth orbit (LEO) satellite or missile communication scenarios, signals may experience extremely large Doppler shifts and have short visual time. Thus, direct sequence spread spectrum (DSSS) systems should be able to achieve acquisition in a very short time in spite of large Doppler frequencies. However, the traditional methods cannot solve it well. This work describes a new method that uses a differential decoding technique for Doppler mitigation and a batch process of FFT (fast Fourier transform) and IFFT (invert FFT) for the purpose of parallel code phase search by frequency domain correlation. After the code phase is estimated, another FFT process is carried out to search the Doppler frequency. Since both code phase and Doppler frequency domains are searched in parallel, this architecture can provide acquisition fifty times faster than conventional FFT methods. The performance in terms of the probability of detection and false alarm are also analyzed and simulated, showing that a signal-to-noise ratio (SNR) loss of 3 dB is introduced by the differential decoding. The proposed method is an efficient way to shorten the acquisition time with slightly hardware increasing.
基金supported in part by the U.S. Department of Agriculture, Agricultural Research Service
文摘Background:The majority of attenuated total reflection Fourier transform infrared(ATR FT-IR)investigations of cotton are focused on the fiber tissue for biological mechanisms and understanding of fiber development and maturity,but rarely on other cotton biomass comp on ents.This work examined in detail the ATR FT-IR spectral features of various cott on tissues/organs at reproductive and maturation stages,an a lyzed and discussed their biological implications.Results:The ATR FT-IR spectra of these tissues/organs were an a lyzed and compared with the focus on the lower wavenumber fingerprinting range.Six outstanding FT-IR bands at 1730,1620,1525,1235,1050 and 895 cm^(-1) represented the major C=O stretching,protein Amide I,Amide II,the O-H/N-H deformation,the total C-O-C stretching and the β-glycosidic linkage in celluloses,respectively,and impacted differently between these organs with the two growth stages.Furthermore,the band intensity at 1620,1525,1235,and 1050 cm^(-1) were exclusively and significantly correlated to the levels of protein(Amide I bond),protein(Amide II bond),cellulose,and hemicellulose,respectively,whereas the band at 1730 cm^(-1) was negatively correlated with ash content.Conclusions:The resulting observations indicated the capability of ATR FT-IR spectroscopy for monitoring changes,transportation,and accumulation of the major chemical components in these tissues over the cotton growth period.In other words,this spectral technology could be an effective tool for physiological,biochemical,and morphological research related to cotton biology and development.
基金the National Natural Science Foundation of China(31201473)the Science and Technology Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS-ASTIP-IVFCAAS)funded by the Key Laboratory of Biology and Genetic Improvement of Horticultural Crops,Ministry of Agriculture,P.R.China
文摘Identification of plant-pathogenic fungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the micro-morphological characters observed.The present investigation aimed to create a simple but sophisticated method for the identification of plant-pathogenic fungi by Fourier transform infrared(FTIR)spectroscopy.In this study,FTIR-attenuated total reflectance(ATR)spectroscopy was used in combination with chemometric analysis for identification of important pathogenic fungi of horticultural plants.Mixtures of mycelia and spores from 27fungal strains belonging to nine different families were collected from liquid PD or solid PDA media cultures and subjected to FTIR-ATR spectroscopy measurements.The FTIR-ATR spectra ranging from 4 000to 400cm-1 were obtained.To classify the FTIRATR spectra,cluster analysis was compared with canonical vitiate analysis(CVA)in the spectral regions of3 050~2 800and 1 800~900cm-1.Results showed that the identification accuracies achieved 97.53%and99.18%for the cluster analysis and CVA analysis,respectively,demonstrating the high potential of this technique for fungal strain identification.
基金Sponsored by National Nature Science Foundation of China(60472101)
文摘The mismatch between echo and replica caused by underwater moving target(UMT)'s radial velocity degrades the detection performance of the matched filter(MF)for the linear frequency modulation(LFM)signal.By using the focusing property of fractional Fourier transform(FRFT)to that signal,a detection algorithm for UMT's LFM echo based on the discrete fractional Fourier transform(DFRFT)is proposed.This algorithm is less affected by the target's radial velocity compared with the other MF detection algorithm utilizing zero radial velocity replica(ZRVR),and the mathematical relation between the output peak positions of these two algorithms exists in the case of existence of target echo.The algorithm can also estimate the target distance by using this relation.The simulation and experiment show that this algorithm'sdetection performance is better than or equivalent to that of the other MF algorithm utilizing ZRVR for the LFM echo of UMT with unknown radial velocity under reverberation noise background.
文摘Fractional Fourier transform(FRFT)is a linear transform generalizing Fourier transform(FT)that plays an important role in the field of signal processing and analysis.FRFT contains an adjustable parameterα,which it rotates the signal in the time frequency plane and represents the signal in an intermediate domain between time and frequency.FRFT provides a measure about the angular distribution of signal’s energy in time frequency plane.FT is a special case of FRFT when angleαis equal toπ/2.This paper presents mathematical model for obtaining FRFT of PC6 window function.The different parameters of this window function are also obtained with the help of simulation results.A comparison of window function parameters is presented using FT and FRFT.Also comparison of this window function with Hanning window function is presented in terms of Side Lobe Fall off Rate(SLFOR).For different values of FRFT order,PC6 window function shows variation in different parameters.Thus by changing the FRFT order,the minimum stop band attenuation of the resulting window function can be controlled.
文摘针对现有深度学习算法在壁画修复时,存在全局语义一致性约束不足及局部特征提取不充分,导致修复后的壁画易出现边界效应和细节模糊等问题,提出一种双向自回归Transformer与快速傅里叶卷积增强的壁画修复方法.首先,设计基于Transformer结构的全局语义特征修复模块,利用双向自回归机制与掩码语言模型(masked language modeling,MLM),提出改进的多头注意力全局语义壁画修复模块,提高对全局语义特征的修复能力.然后,构建了由门控卷积和残差模块组成的全局语义增强模块,增强全局语义特征一致性约束.最后,设计局部细节修复模块,采用大核注意力机制(large kernel attention,LKA)与快速傅里叶卷积提高细节特征的捕获能力,同时减少局部细节信息的丢失,提升修复壁画局部和整体特征的一致性.通过对敦煌壁画数字化修复实验,结果表明,所提算法修复性能更优,客观评价指标均优于比较算法.
基金Project supported by the Second Stage of Brain Korea 21 Projects
文摘Fault detection of an induction motor was carried out using the information of the stator current. After synchronizing the actual data, Fourier and wavelet transformations were adopted in order to obtain the sideband or detail value characteristics under healthy and various faulty operating conditions. The most reliable phase current among the three phase currents was selected using an approach that employs the fuzzy entropy measure. Data were trained with a neural network system, and the fault detection algorithm was verified using the unknown data. Results of the proposed approach based on Fourier and wavelet transformations indicate that the faults can be properly classified into six categories. The training error is 5.3×10-7, and the average test error is 0.103.
