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| 1 | 小波分析在激光多普勒信号处理中的应用显示文摘提出将激光多普勒测速仪(LDV)应用于车载惯性导航系统中,阐述了激光多普勒自身速度仪的基本原理和小波变换的相关理论,并运用小波变换对多普勒信号进行检测、去噪及提取多普勒频率,仿真及实验结果表明:信号进行小波分解后,对每一级小波进行阈值处理,得到了较好的去噪效果;在小波降噪常见的阈值原则中,无偏似然估计阈值和极值阈值不容易丢失信号中的有用成分,而启发式阈值原则和固定阈值原则可以更有效地去除噪声;对于提取多普勒频率而言,小波变换与快速傅里叶变换所得的结果是一致的,而小波变换不但可以求出系统自身的运动速度,而且还可以求出对应速度发生的时刻。 | 周健 龙兴武 | 2010 | 强激光与粒子束2010，22，12： | 7 |
| 2 | Matched field noise suppression: Principle with application to towed hydrophone line array显示文摘Discrete noise source suppression in underwa-ter acoustic channel has attracted great attention in recent years. The paper proposes a new principle for dealing with the problem. This new principle is called matched field noise suppression (MFNS). Based on a previous work of the au-thors group, a full understanding about how a discrete noise source shows effects on the performance of a towed hydro-phone line array has been obtained. In light of that finding, MFNS is proposed, which explores and utilizes the charac-teristics of the noise transmission channel to achieve much greater suppression of the noise in comparison with existing approaches. MFNS combines the concept of matched field processing (MFP) and optimal sensor array processing (OSAP) together to suppress the discrete noise source and to maintain an optimal beam for receiving far-field wanted plane wave signals. A MFNS beam-former is deduced in constraint with signal plane-wave response being unit and noise matched field response being zero. A closed-form solution of the weight vec-tor for the beam-former is given. Computer simulation results agree well to the theoretical analysis. | MA Yuanliang YAN Shefeng YANG Kunde | 2003 | Chinese Science Bulletin2003，48，12： | 4 |
| 3 | Wavelet analysis and its application to signal processing显示文摘The construction of basic wavelet was discussed and many basic analyzing wavelets was compared. Acomplex analyzing wavelet which is continuous, smoothing, orthogonal and exponential decreasing was presented, andit was used to decompose two blasting seismic signals with the continuous wavelet transforms (CWT). The resultshows that wavelet analysis is the better method to help us determine the essential factors which create damage effectsthan Fourier analysis. | HE Jun WU Yalun (Resource Engineering School, University of Science and Technology Beijing, Beijing 100083, China) | 1997 | International Journal of Minerals,Metallurgy and Materials1997，11，3： | 4 |
| 4 | Review of local mean decomposition and its application in fault diagnosis of rotating machinery显示文摘Rotating machinery is widely used in the industry.They are vulnerable to many kinds of damages especially for those working under tough and time-varying operation conditions.Early detection of these damages is important,otherwise,they may lead to large economic loss even a catastrophe.Many signal processing methods have been developed for fault diagnosis of the rotating machinery.Local mean decomposition(LMD)is an adaptive mode decomposition method that can decompose a complicated signal into a series of mono-components,namely product functions(PFs).In recent years,many researchers have adopted LMD in fault detection and diagnosis of rotating machines.We give a comprehensive review of LMD in fault detection and diagnosis of rotating machines.First,the LMD is described.The advantages,disadvantages and some improved LMD methods are presented.Then,a comprehensive review on applications of LMD in fault diagnosis of the rotating machinery is given.The review is divided into four parts:fault diagnosis of gears,fault diagnosis of rotors,fault diagnosis of bearings,and other LMD applications.In each of these four parts,a review is given to applications applying the LMD,improved LMD,and LMD-based combination methods,respectively.We give a summary of this review and some future potential topics at the end. | LI Yongbo SI Shubin LIU Zhiliang LIANG Xihui | 2019 | Journal of Systems Engineering and Electronics2019，30，4： | 4 |
| 5 | Application of spline wavelet transform in differential of electroanalytical signal显示文摘Investigating characteristics of spline wavelet, we found that if the two-order spline function, the derivative function of the three-order B spline function, is used as the wavelet base function, the spline wavelet transform has both the property of denoising and that of differential. As a result, the relation between the spline wavelet transform and the differential was studied in theory. Experimental results show that the spline wavelet transform can well be applied to the differential of the electroanalytical signal. Compared with other kinds of wavelet transform, the spline wavelet transform has a characteristic of differential. Compared with the digital differentia] and simulative differential with electronic circuit, the spline wavelet transform not only can carry out denoising and differential for a signal, but also has the advantages of simple operation and small quantity of calculation, because step length, RC constant and other kinds of parameters need not be selected. Compared with | ZHANG Shuling ZHENG Jianbin GU Wenliang ZHANG Hongquan HOU Xun GAO Hong | 2001 | Chinese Science Bulletin2001，46，7： | 3 |
| 6 | Applications of advanced signal processing and machine learning in the neonatal hypoxic-ischemic electroencephalography显示文摘Perinatal hypoxic-ischemic-encephalopathy significantly contributes to neonatal death and life-long disability such as cerebral palsy. Advances in signal processing and machine learning have provided the research community with an opportunity to develop automated real-time identification techniques to detect the signs of hypoxic-ischemic-encephalopathy in larger electroencephalography/amplitude-integrated electroencephalography data sets more easily. This review details the recent achievements, performed by a number of prominent research groups across the world, in the automatic identification and classification of hypoxic-ischemic epileptiform neonatal seizures using advanced signal processing and machine learning techniques. This review also addresses the clinical challenges that current automated techniques face in order to be fully utilized by clinicians, and highlights the importance of upgrading the current clinical bedside sampling frequencies to higher sampling rates in order to provide better hypoxic-ischemic biomarker detection frameworks. Additionally, the article highlights that current clinical automated epileptiform detection strategies for human neonates have been only concerned with seizure detection after the therapeutic latent phase of injury. Whereas recent animal studies have demonstrated that the latent phase of opportunity is critically important for early diagnosis of hypoxic-ischemic-encephalopathy electroencephalography biomarkers and although difficult, detection strategies could utilize biomarkers in the latent phase to also predict the onset of future seizures. | Hamid Abbasi Charles P.Unsworth | 2020 | Neural Regeneration Research2020，15，2： | 3 |
| 7 | Frequency Loss and Recovery in Rolling Bearing Fault Detection显示文摘Rolling element bearings are key components of mechanical equipment. The bearing fault characteristics are a ected by the interaction in the vibration signals. The low harmonics of the bearing characteristic frequencies cannot be usually observed in the Fourier spectrum. The frequency loss in the bearing vibration signal is presented through two independent experiments in this paper. The existence of frequency loss phenomenon in the low frequencies, side band frequencies and resonant frequencies and revealed. It is demonstrated that the lost frequencies are actually suppressed by the internal action in the bearing fault signal rather than the external interference. The amplitude and distribution of the spectrum are changed due to the interaction of the bearing fault signal. The interaction mechanism of bearing fault signal is revealed through theoretical and practical analysis. Based on mathematical morphology, a new method is provided to recover the lost frequencies. The multi-resonant response signal of the defective bearing are decomposed into low frequency and high frequency response, and the lost frequencies are recovered by the combination morphological filter(CMF). The e ectiveness of the proposed method is validated on simulated and experimental data. | Aijun Hu Ling Xiang Sha Xu Jianfeng Lin | 2019 | Chinese Journal of Mechanical Engineering2019，32，2： | 3 |
| 8 | Modeling and realization of real time electronic countermeasure simulation system based on SystemVue显示文摘In this paper,we proposed a new design scheme of real time electronic countermeasure simulation system.This paper mainly expounds the modeling and realization methods of each part of the whole simulation system,and the real-time property of system has been lucubrated.Electronic countermeasure simulation system is the key part of military training of individuals;it can also allow the realistic evaluation of the performance of modern equipments and techniques.As a proof,we have drawn up a series of simulation scenarios,such as radar electronic reconnaissance simulation scenario,to explain the feasibility and the superiority of our modeling scheme in this paper. | Xiao-rong Tong | 2020 | Defence Technology(防务技术)2020，16，2： | 3 |
| 9 | A Modified Root-MUSIC Algorithm for Signal DOA Estimation显示文摘This paper presents a modified Root-MUSIC algorithm by which the signal DOA estimation performance can be improved when the snapshot number is limited. The operation principlesof this algorithm are described in detail. It is also pointed out theoretically that this is equivalentto have increased the snapshot number and can make the DOA estimation better. Finally, somesimulating results to verify the theoretical analyses are presented. | He Zishu Li Yong & Xiang Jingcheng(Institute of Electronic Engineering, University of Electronic Science & Technology,Chengdu 610054, P. R. China) | 1999 | Journal of Systems Engineering and Electronics1999，10，4： | 2 |
| 10 | Wavelet-Fourier self-deconvolution显示文摘Using a wavelet function as the filter function of Fourier self-deconvolution, a new method of resolving overlapped peaks, wavelet-Fourier self-deconvolution, is founded. The properties of different wavelet deconvolution functions are studied. In addition, a cutoff value coefficient method of eliminating artificial peaks and wavelet method of removing shoulder peaks using the ratio of maximum peak to minimum peak is established. As a result, some problems in classical Fourier self-deconvolution are solved, such as the bad result of denoising, complicated processing, as well as usual appearance of artificial and shoulder peaks. Wavelet-Fourier self-deconvolution is applied to determination of multi-components in oscillographic chronopotentiometry. Experimental results show that the method has characteristics of simpler process and better effect of processing. | 郑建斌 张红权 高鸿 | 2000 | Science China Chemistry2000，43，1： | 2 |
| 11 | Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System显示文摘It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems,which shows promise in home healthcare, rescue, and security applications. In this paper, we first present a multi-ray propagation model for UWB signal, which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces. A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment. This model enables replication of time-varying multipath profiles due to the displacement of a human chest. Subsequently,a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate. The analytical framework can serve as a basis in the planning and evaluation of future measurement programs. We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture. | Predrag Rapajic | 2008 | International Journal of Automation and computing2008，5，4： | 2 |
| 12 | Improvement of Boxcar Integrator and Its Application to Low Resistance Measurement of Inductive Load Coil显示文摘A boxcar integrator is described which is suitable for the low-repetition-rate signal processing. This boxcar integrator, named fixed-interval mode boxcar integrator, is able to reject harmonics other than the first harmonic component. It can also decrease the effective time constant In many situations, the antialiasing filter with narrow bandwidth will cause distortion of the input signal. The fixed-interval mode boxcar integrator with suitable gate width can achieve relative high performance without signal distortion because the bandwidth of its antialiasing filter can be wider than that in the fixed-Point boxcar integrator. ms boxcar integrator is used as majn part of signalprocessing circult in the low resisance measurement of inductive load coil. The results of experiments show that the fixed-interval boxcar integrator is suitable for low-repetition-rate use. | Xisheng Li Shaochun Wang(Information Engineering School, University of Science and Technology Beijing, Beijing 100083, China) | 1998 | International Journal of Minerals,Metallurgy and Materials1998，12，3： | 2 |
| 13 | 2-D DIRECTION FINDING OF COHERENT SIGNALS VIA TEMPORO-SPATIAL PROCESSING显示文摘In most wireless communication systems, two-dimensional Directions-Of-Arrival (DOA) of multipath signals need to be found for spatial selective transmission. However, it is quite difficult to find their DOAs due to the coherent nature of multipath signals and considerable computations when performing 2-D searches. In this paper, a new algorithm to estimate 2-D DOA of multiple narrow-band signals is proposed. A DOA cyclic matrix is constructed whose eigenvalues and eigenvectors can be simultaneously used to extract 2-D DOA without 2-D searches. By exploiting the temporal property of cyclostationarity, the signal detection capability is significantly improved. Besides, based on the decorrelation model for mobile terminal signals, the algorithm can be effectively extended to the coherent case without spatial smoothing and the loss of array aperture. Simulation results are given to illustrate the performance of the new algorithm. | Jin Liang (PLA Information Engineering College, 1001 P. O. Box 6-5#, Zhengzhou 450002)Yao Minli Yin Qinye (Institute of Information Engineering, Xi’an Jiaotong University, Xi’an, 710049) | 2000 | Journal of Electronics(China)2000，17，1： | 2 |
| 14 | Novel Biological Based Method for Robot Navigation and Localization显示文摘The capability and reliability are crucial characteristics of mobile robots while navigating in complex environments. These robots are expected to perform many useful tasks which can improve the quality of life greatly. Robot localization and decisionmaking are the most important cognitive processes during navigation. However, most of these algorithms are not efficient and are challenging tasks while robots navigate through complex environments. In this paper,we propose a biologically inspired method for robot decision-making, based on rat's brain signals. Rodents accurately and rapidly navigate in complex spaces by localizing themselves in reference to the surrounding environmental landmarks. Firstly, we analyzed the rats' strategies while navigating in the complex Y-maze, and recorded local field potentials(LFPs), simultaneously.The recorded LFPs were processed and different features were extracted which were used as the input in the artificial neural network(ANN) to predict the rat's decision-making in each junction. The ANN performance was tested in a real robot and good performance is achieved. The implementation of our method on a real robot, demonstrates its abilities to imitate the rat's decision-making and integrate the internal states with external sensors, in order to perform reliable navigation in complex maze. | Endri Rama Genci Capi Yusuke Fujimura Norifumi Tanaka Shigenori Kawahara Mitsuru Jindai | 2018 | Journal of Electronic Science and Technology2018，16，1： | 2 |
| 15 | Fast-convolution multicarrier based frequency division multiple access显示文摘Fast-convolution multicarrier(FCMC), the asynchronous waveform with ultra-low sidelobe, has appeared to be a promising waveform technique for future wireless communications. In this paper, we investigate the filter bank optimization as well as receiver design including low-complexity channel estimator and equalizer for FCMC based frequency division multiple access(FDMA). Starting from the conventional multi-carrier signals, we first derive a vectorized signal model as a framework to systematically design the FCMC transceiver. For nearly perfect reconstruction(NPR) filter banks design, an optimization criterion which consists of minimizing received signal segments’ mean square error(MSE) is proposed. From the fact that Toeplitz matrices can be asymptotically diagonalized by discrete Fourier transform(DFT) matrix, the channel equalizer can be simplified to one-tap frequency domain equalizer when DFT size is large enough.The minimum mean square error(MMSE) criterion is then applied to calculate the coefficients of onetap frequency domain equalizer. In practice, due to the channel fading, the channel estimation has to be performed to obtain the channel state information(CSI) which is required by the channel equalization. To this end, we propose a combined cyclic prefix(CP) and cyclic suffix(CS) pilot structure which facilitates to estimate the frequency domain CSI directly in the receiver end. The proposed FCMC based FDMA features low-complexity receiver, adjustable users’ bandwidth and low peak-to-average power ratio. Simulation results confirm the performance of the proposed scheme. | Yining LI Wenjin WANG Jiaheng WANG Xiqi GAO | 2019 | Science China(Information Sciences)2019，62，8： | 2 |
| 16 | Research on Anti-noise Processing Method of Production Signal Based on Ensemble Empirical Mode Decomposition(EEMD)显示文摘The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction. | Fang Jun-long Yu Xiao-juan Wang Rui-fa Wang Run-tao Li Peng-fei Shao Chang-hui | 2017 | Journal of Northeast Agricultural University(English Edition)2017，24，4： | 2 |
| 17 | A 2-step GPS carrier tracking loop for urban vehicle applications显示文摘Global positioning system(GPS) for vehicle applications in the urban area is challenged by low signal intensity. The carrier loop based on fast Fourier transform(FFT) can obtain a high signal to noise ratio(SNR) gain by increasing the observation time. However, this leads to a major problem that the acceleration cannot be ignored. The performance of the FFT-based loop will decline with the acceleration increasing. This paper discusses the effect of the dynamic on FFT first. Then a high performance carrier tracking loop for weak GPS L5 signals is proposed. It combines discrete chirp-Fourier transform(DCFT) and the phase fitting method to estimate Doppler frequency and Doppler rate simultaneously.First, a sequence of integration results is used to perform DCFT to estimate coarse Doppler frequency and Doppler rate. Second, the phase of the sequence is calculated and used to perform linear fitting. By the phase fitting method, the fine Doppler frequency and Doppler rate can be estimated. The computation cost is small because the integration results are used and the phase fitting method needs only coarse estimates of Doppler frequency and Doppler rate. Compared with FFT and DCFT, the precision of the phase fitting method is not limited by the resolution. Thus the proposed loop can get high precision and low carrier to noise ratio(C/N0) tracking threshold. Simulation results show this loop has a great improvement than conventional loops for urban weak-signal applications. | Hongyang Zhang Luping Xu Yue Jian Xiaochen Ma | 2017 | Journal of Systems Engineering and Electronics2017，28，5： | 1 |
| 18 | Survey on Encoding Schemes for Genomic Data Representation and Feature Learning——From Signal Processing to Machine Learning显示文摘Data-driven machine learning, especially deep learning technology, is becoming an important tool for handling big data issues in bioinformatics. In machine learning, DNA sequences are often converted to numerical values for data representation and feature learning in various applications. Similar conversion occurs in Genomic Signal Processing(GSP), where genome sequences are transformed into numerical sequences for signal extraction and recognition. This kind of conversion is also called encoding scheme. The diverse encoding schemes can greatly affect the performance of GSP applications and machine learning models. This paper aims to collect,analyze, discuss, and summarize the existing encoding schemes of genome sequence particularly in GSP as well as other genome analysis applications to provide a comprehensive reference for the genomic data representation and feature learning in machine learning. | Ning Yu Zhihua Li Zeng Yu | 2018 | Big Data Mining and Analytics2018，1，3： | 1 |
| 19 | Eigenvalue spectrum analysis for temporal signals of Kerr optical frequency combs based on nonlinear Fourier transform显示文摘Based on the nonlinear Schr?dinger equation(NLSE) with damping, detuning, and driving terms describing the evolution of signals in a Kerr microresonator, we apply periodic nonlinear Fourier transform(NFT) to the study of signals during the generation of the Kerr optical frequency combs(OFCs). We find that the signals in different states, including the Turing pattern, the chaos, the single soliton state, and the multi-solitons state, can be distinguished according to different distributions of the eigenvalue spectrum. Specially, the eigenvalue spectrum of the single soliton pulse is composed of a pair of conjugate symmetric discrete eigenvalues and the quasi-continuous eigenvalue spectrum with eye-like structure.Moreover, we have successfully demonstrated that the number of discrete eigenvalue pairs in the eigenvalue spectrum corresponds to the number of solitons formed in a round-trip time inside the Kerr microresonator. This work shows that some characteristics of the time-domain signal can be well reflected in the nonlinear domain. | 王佳 盛爱国 黄鑫 李荣玉 何广强 | 2020 | Chinese Physics B2020，29，3： | 1 |
| 20 | NEW METHOD FOR REDUCED RANK STAP—NON CLUTTER CHANNEL METHOD显示文摘For reduced rank space time adaptive processing(STAP) in airborne radar, this paper presents a new method — non clutter channel(NCC) method which is easy to implement in real radar systems. The NCC method uses those “channels” located in the non clutter domain to construct the reduce rank transformation matrix. This method avoids eigen decomposition and the computational cost is very low. The performance is compared with that of several other methods; the simulation demonstrates that the NCC method can well approach the optimum performance and even outperform some more complex methods in low rank. | 王玮 李少洪 毛士艺 | 2000 | Chinese Journal of Aeronautics2000，13，4： | 1 |
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