Fires and human casualties caused by single phase-to-ground faults in distribution networks are frequent.However,existing ground fault suppression methods are affected by ground fault resistance.Thus,an adaptive suppr...Fires and human casualties caused by single phase-to-ground faults in distribution networks are frequent.However,existing ground fault suppression methods are affected by ground fault resistance.Thus,an adaptive suppression method that seamlessly combines principles of current and voltage suppression is proposed,which has good adaptability to different ground fault resistance.Meanwhile,a multi-criteria ground fault suppression exit strategy matched to adaptive suppression method is proposed to avoid damage of device caused by power backflow,which provides the possibility for reliable and fast exit of the fault suppression device.Experimental results demonstrate effectiveness and advantages of the adaptive suppression method and its exit strategy.展开更多
Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the phy...Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.展开更多
Optical coherence tomography(OCT),particularly Swept-Source OCT,is widely employed in medical diagnostics and industrial inspections owing to its high-resolution imaging capabilities.However,Swept-Source OCT 3D imagin...Optical coherence tomography(OCT),particularly Swept-Source OCT,is widely employed in medical diagnostics and industrial inspections owing to its high-resolution imaging capabilities.However,Swept-Source OCT 3D imaging often suffers from stripe artifacts caused by unstable light sources,system noise,and environmental interference,posing challenges to real-time processing of large-scale datasets.To address this issue,this study introduces a real-time reconstruction system that integrates stripe-artifact suppression and parallel computing using a graphics processing unit.This approach employs a frequency-domain filtering algorithm with adaptive anti-suppression parameters,dynamically adjusted through an image quality evaluation function and optimized using a convolutional neural network for complex frequency-domain feature learning.Additionally,a graphics processing unit integrated 3D reconstruction framework is developed,enhancing data processing throughput and real-time performance via a dual-queue decoupling mechanism.Experimental results demonstrate significant improvements in structural similarity(0.92),peak signal-to-noise ratio(31.62 dB),and stripe suppression ratio(15.73 dB)compared with existing methods.On the RTX 4090 platform,the proposed system achieved an end-to-end delay of 94.36 milliseconds,a frame rate of 10.3 frames per second,and a throughput of 121.5 million voxels per second,effectively suppressing artifacts while preserving image details and enhancing real-time 3D reconstruction performance.展开更多
The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the tradit...The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the traditional linear regression approach. However, the existing 2D U-net approach with 2D data windows can not deal with elaborate discrepancies between the actual and simulated multiples along the gather direction. It may lead to erroneous preservation of primaries or generate obvious vestigial multiples, especially in complex media. To further enhance the multiple suppression accuracy, we present an adaptive subtraction approach utilizing 3D U-net architecture, which can adaptively separate primaries and multiples utilizing 3D windows. The utilization of 3D windows allows for enhanced depiction of spatial continuity and anisotropy of seismic events along the gather direction in comparison to 2D windows. The 3D U-net approach with 3D windows can more effectively preserve the continuity of primaries and manage the complex disparities between the actual and simulated multiples. The proposed 3D U-net approach exhibits 1 dB improvement in the signal-to-noise ratio compared to the 2D U-net approach, as observed in the synthesis data section, and exhibits more outstanding performance in the preservation of primaries and removal of residual multiples in both synthesis and reality data sections. Moreover, to expedite network training in our proposed 3D U-net approach we employ the transfer learning (TL) strategy by utilizing the network parameters of 3D U-net estimated in the preceding data segment as the initial network parameters of 3D U-net for the subsequent data segment. In the reality data section, the 3D U-net approach incorporating TL reduces the computational expense by 70% compared to the one without TL.展开更多
The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deterior...The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deteriorates greatly when the FM inter- ference power exceeds the anti-jamming limit of the radar. Accord- ing to the fact that the PRC-CW radar echo is a wideband pseudo random signal occupying the whole TF plane, while the FM in- terference only concentrates in a small portion, a new method is proposed based on adaptive short-time Fourier transform （STFT） and time-varying filtering for FM interference suppression. This method filters the received signal by using a binary mask to excise only the portion of the TF plane corrupted by the interference. Two types of interference, linear FM （LFM） and sinusoidal FM （SFM）, under different signal-to-jamming ratio （S JR） are studied. It is shown that the proposed method can effectively suppress the FM interference and improve the performance of target detection.展开更多
Visual background extraction algorithm(ViBe)uses the first frame image to initialize the background model,which can easily introduce the“ghost”.Because ViBe uses the fixed segmentation threshold to achieve the foreg...Visual background extraction algorithm(ViBe)uses the first frame image to initialize the background model,which can easily introduce the“ghost”.Because ViBe uses the fixed segmentation threshold to achieve the foreground and background segmentation,the detection results in many false detections for the highly dynamic background.To solve these problems,an improved ghost suppression and adaptive Visual Background Extraction algorithm is proposed in this paper.Firstly,with the pixel’s temporal and spatial information,the historical pixels of a certain combination are used to initialize the background model in the odd frames of the video sequence.Secondly,the background sample set combined with the neighborhood pixels are used to determine a complex degree of the background,to acquire the adaptive segmentation threshold.Thirdly,the update rate is adjusted based on the complexity of the background.Finally,the detected result goes through a post-processing to achieve better detection results.The experimental results show that the improved algorithm will not only quickly suppress the“ghost”,but also have a better detection in a complex dynamic background.展开更多
Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.I...Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.展开更多
For the performance issues of satellite transceivers suffering passive intermodulation interference,a novel and effective digital suppression algorithm is presented in this paper.In contrast to analog approaches,digit...For the performance issues of satellite transceivers suffering passive intermodulation interference,a novel and effective digital suppression algorithm is presented in this paper.In contrast to analog approaches,digital passive intermodulation（PIM） suppression approaches can be easily reconfigured and therefore are highly attractive for future satellite communication systems.A simplified model of nonlinear distortion from passive microwave devices is established in consideration of the memory effect.The multiple high-order PIM products falling into the receiving band can be described as a bilinear predictor function.A suppression algorithm based on a bilinear polynomial decorrelated adaptive filter is proposed for baseband digital signal processing.In consideration of the time-varying characteristics of passive intermodulation,this algorithm can achieve the rapidness of online interference estimation and low complexity with less consumption of resources.Numerical simulation results show that the algorithm can effectively compensate the passive intermodulation interference,and achieve a high signal-to-interference ratio gain.展开更多
In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information ...In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information in the intensity image to estimate the illumination. After locating the points, the whole illumination image was computed by an interpolation technique. When attempting to recover the reflectance image, an adaptive method which can be considered as an optimization problem was employed to suppress noise in dark environments and keep details in other areas. For color images, it was taken in the band of each channel separately. Experimental results demonstrate that the proposed algorithm is superior to the traditional Retinex algorithms in image entropy.展开更多
Active Magnetic Bearing(AMB) is a kind of electromagnetic support that makes the rotor movement frictionless and can suppress rotor vibration by controlling the magnetic force. The most common approach to restrain the...Active Magnetic Bearing(AMB) is a kind of electromagnetic support that makes the rotor movement frictionless and can suppress rotor vibration by controlling the magnetic force. The most common approach to restrain the rotor vibration in AMBs is to adopt a notch filter or adaptive filter in the AMB controller. However, these methods cannot obtain the precise amplitude and phase of the compensation current. Thus, they are not so effective in terms of suppressing the vibrations of the fundamental and other harmonic orders over the whole speed range. To improve the vibration suppression performance of AMBs,an adaptive filter based on Least Mean Square(LMS) is applied to extract the vibration signals from the rotor displacement signal. An Iterative Search Algorithm(ISA) is proposed in this paper to obtain the corresponding relationship between the compensation current and vibration signals. The ISA is responsible for searching the compensating amplitude and shifting phase online for the LMS filter, enabling the AMB controller to generate the corresponding compensation force for vibration suppression. The results of ISA are recorded to suppress vibration using the Look-Up Table(LUT) in variable speed range. Comprehensive simulations and experimental validations are carried out in fixed and variable speed range, and the results demonstrate that by employing the ISA, vibrations of the fundamental and other harmonic orders are suppressed effectively.展开更多
The negative impact on communication performance in wireless multi-hop communication net-work caused by limited bandwidth,high bit eror rate （BER）,fading,noise and interference is alleviated by an adaptive filtering...The negative impact on communication performance in wireless multi-hop communication net-work caused by limited bandwidth,high bit eror rate （BER）,fading,noise and interference is alleviated by an adaptive filtering game based on frequency subbands selection and predetemined threshold.Such threshold is being obtained in Gaussian and multipath fading channel according to the frequency-matching principle and BER performance.The dynamic selection of subbands will obtain high use efficiency without the help of frequency hopping,and propound a new thought to improve band limited communication for wireless multi-hop communication network.The effectiveness of the adaptive filtering method has been verified by interleaving spread spectrum orthogonal frequency division multiplexing （ISS-OFDM） in different interference conditions,and the simulating results based on network simulator 2 （NS2） indicate that system BER can be improved greatly.展开更多
A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the s...A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.展开更多
Regulation plays a pivotal role in mitigating the spread of rumors, serving as a vital tool for maintaining social stability and facilitating its evolution. A central challenge lies in establishing an effective regula...Regulation plays a pivotal role in mitigating the spread of rumors, serving as a vital tool for maintaining social stability and facilitating its evolution. A central challenge lies in establishing an effective regulatory framework despite limited resources available for combating rumor propagation. To address this challenge, this paper proposes a dynamic and adaptive regulatory system. First, based on observed regulatory patterns in real-world social networks, the rumor propagation process is divided into two distinct phases: regulation and intervention. Regulatory intensity is introduced as an indicator of user state transitions. Unlike traditional, non-adaptive regulatory models that allocate costs uniformly,the adaptive model facilitates flexible cost distribution through a manageable individual regulatory intensity. Moreover,by introducing adaptive strength, the two cost allocation models are integrated within a unified framework, leading to the development of a dynamic model for rumor suppression. Finally, simulation experiments on Barabási–Albert(BA)networks demonstrate that the adaptive regulatory mechanism significantly reduces both the scope and duration of rumor propagation. Furthermore, when traditional non-adaptive regulatory models show limited effectiveness, the adaptive model effectively curbs rumor propagation by optimizing cost allocation between regulatory and intervention processes, and by adjusting per-unit cost benefit differentials.展开更多
The influence of intracortical inhibition on the response adaptation of visual cortical neurons remains in debate. To clarify this issue, in the present study the influence of surround suppression evoked through the l...The influence of intracortical inhibition on the response adaptation of visual cortical neurons remains in debate. To clarify this issue, in the present study the influence of surround suppression evoked through the local inhibitory interneurons on the adaptation effects of neurons in the primary visual cortex （V1） were observed. Moreover, the adaptations of V1 neurons to both the high-contrast visual stimuli presented in the classical receptive field （CRF） and to the costimulation presented in the CRF and the surrounding nonclassical receptive field （nCRF） were compared. The intensities of surround suppression were modulated with different sized grating stimuli. The results showed that the response adaptation of V1 neurons decreased significantly with the increase of surround suppression and this adaptation decrease was due to the reduction of the initial response of V1 neurons to visual stimuli. However, the plateau response during adaptation showed no significant changes. These findings indicate that the adaptation effects of V1 neurons may not be directly affected by surround suppression, but may be dynamically regulated by a negative feedback network and be finely adjusted by its initial spiking response to stimulus. This adaptive regulation is not only energy efficient for the central nervous system, but also beneficially acts to maintain the homeostasis of neuronal response to long-presenting visual signals.展开更多
In deep learning super-resolution microscopy,concerns exist about the generation of artifacts,and methods for artifact suppression are lacking.We developed a self-adaptive fine-tuning method that dynamically adjusts t...In deep learning super-resolution microscopy,concerns exist about the generation of artifacts,and methods for artifact suppression are lacking.We developed a self-adaptive fine-tuning method that dynamically adjusts the parameters of the models to minimize the loss function,which includes direct quantification of artifacts from live-cell imaging.Integrating self-adaptive fine-tuning with super-resolution models enables significant arti-fact reduction in the visualization of nanoscale organelle interactions at high spatial-temporal resolution.展开更多
To improve the data quality of converted waves, and better identify and suppress the strong ground-roll interference in three-component （3C） seismic recordings on land, we present an adaptive polarization filtering ...To improve the data quality of converted waves, and better identify and suppress the strong ground-roll interference in three-component （3C） seismic recordings on land, we present an adaptive polarization filtering method, which can effectively separate the ground- roll interference by combining complex polarization and instantaneous polarization analysis. The ground roll noise is characterized by elliptical plane polarization, strong energy, low apparent velocity, and low frequency. After low-pass filtering of the 3C data input within a given time-window of the ground roll, the complex covariance matrix is decomposed using the sliding time window with overlapping data and length that depends on the dominant ground-roll frequency. The ground-roll model is established using the main eigenvectors, and the ground roll is detected and identified using the instantaneous polarization area attributes and average energy constraints of the ground-roll zone. Finally, the ground roll is subtracted. The threshold of the method is stable and easy to select, and offers good ground- roll detection. The method is a robust polarization filtering method. Model calculations and actual data indicate that the method can effectively identify and attenuate ground roll while preserving the effective signals.展开更多
One of the aerodynamic phenomena associated with high performance aircraft is the high frequency vortex induced buffeting. The buffeting load can lead to high cyclic strain and stress,dramatically reduce the fatigue ...One of the aerodynamic phenomena associated with high performance aircraft is the high frequency vortex induced buffeting. The buffeting load can lead to high cyclic strain and stress,dramatically reduce the fatigue life of composite structures. In this paper, piezoelectric patches are bonded on the surface of composite panel. The dynamic response of the structure is measured by using bonded piezoelectric sensors. Filtered adaptive control algorithm is used to control the strain of piezoelectric actuators actively, so as to increase the modal damping coefficient of the composite panel, suppress the dynamic response and improve the fatigue performance of the structure. The feasibility of this method is verified in model experiments.展开更多
A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon a...A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon approach . It is of practical use for its small computational load. This approach possesses the ideal performance in the area of main-lobe clutter . In addition, the approach which is added by some auxiliary beams in the area of main-lobe clutter has also been discussed.展开更多
In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristi...In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.展开更多
A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamical...A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.展开更多
基金supported by the National Natural Science Foundation of China(51677030).
文摘Fires and human casualties caused by single phase-to-ground faults in distribution networks are frequent.However,existing ground fault suppression methods are affected by ground fault resistance.Thus,an adaptive suppression method that seamlessly combines principles of current and voltage suppression is proposed,which has good adaptability to different ground fault resistance.Meanwhile,a multi-criteria ground fault suppression exit strategy matched to adaptive suppression method is proposed to avoid damage of device caused by power backflow,which provides the possibility for reliable and fast exit of the fault suppression device.Experimental results demonstrate effectiveness and advantages of the adaptive suppression method and its exit strategy.
基金supported by the National Natural Science Foundation of China under Grant 62301051.
文摘Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.
文摘Optical coherence tomography(OCT),particularly Swept-Source OCT,is widely employed in medical diagnostics and industrial inspections owing to its high-resolution imaging capabilities.However,Swept-Source OCT 3D imaging often suffers from stripe artifacts caused by unstable light sources,system noise,and environmental interference,posing challenges to real-time processing of large-scale datasets.To address this issue,this study introduces a real-time reconstruction system that integrates stripe-artifact suppression and parallel computing using a graphics processing unit.This approach employs a frequency-domain filtering algorithm with adaptive anti-suppression parameters,dynamically adjusted through an image quality evaluation function and optimized using a convolutional neural network for complex frequency-domain feature learning.Additionally,a graphics processing unit integrated 3D reconstruction framework is developed,enhancing data processing throughput and real-time performance via a dual-queue decoupling mechanism.Experimental results demonstrate significant improvements in structural similarity(0.92),peak signal-to-noise ratio(31.62 dB),and stripe suppression ratio(15.73 dB)compared with existing methods.On the RTX 4090 platform,the proposed system achieved an end-to-end delay of 94.36 milliseconds,a frame rate of 10.3 frames per second,and a throughput of 121.5 million voxels per second,effectively suppressing artifacts while preserving image details and enhancing real-time 3D reconstruction performance.
基金supported by National Natural Science Foundation of China(42364008,41804110)in part by Guizhou Provincial Basic Research Program(Natural Science)(ZK[2022]060)+1 种基金in part by China Postdoctoral Science Foundation(2022M723127)in part by Youth Innovation Team Project of Shandong Provincial Education Department(2022KJ141).
文摘The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the traditional linear regression approach. However, the existing 2D U-net approach with 2D data windows can not deal with elaborate discrepancies between the actual and simulated multiples along the gather direction. It may lead to erroneous preservation of primaries or generate obvious vestigial multiples, especially in complex media. To further enhance the multiple suppression accuracy, we present an adaptive subtraction approach utilizing 3D U-net architecture, which can adaptively separate primaries and multiples utilizing 3D windows. The utilization of 3D windows allows for enhanced depiction of spatial continuity and anisotropy of seismic events along the gather direction in comparison to 2D windows. The 3D U-net approach with 3D windows can more effectively preserve the continuity of primaries and manage the complex disparities between the actual and simulated multiples. The proposed 3D U-net approach exhibits 1 dB improvement in the signal-to-noise ratio compared to the 2D U-net approach, as observed in the synthesis data section, and exhibits more outstanding performance in the preservation of primaries and removal of residual multiples in both synthesis and reality data sections. Moreover, to expedite network training in our proposed 3D U-net approach we employ the transfer learning (TL) strategy by utilizing the network parameters of 3D U-net estimated in the preceding data segment as the initial network parameters of 3D U-net for the subsequent data segment. In the reality data section, the 3D U-net approach incorporating TL reduces the computational expense by 70% compared to the one without TL.
文摘The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deteriorates greatly when the FM inter- ference power exceeds the anti-jamming limit of the radar. Accord- ing to the fact that the PRC-CW radar echo is a wideband pseudo random signal occupying the whole TF plane, while the FM in- terference only concentrates in a small portion, a new method is proposed based on adaptive short-time Fourier transform （STFT） and time-varying filtering for FM interference suppression. This method filters the received signal by using a binary mask to excise only the portion of the TF plane corrupted by the interference. Two types of interference, linear FM （LFM） and sinusoidal FM （SFM）, under different signal-to-jamming ratio （S JR） are studied. It is shown that the proposed method can effectively suppress the FM interference and improve the performance of target detection.
基金Project(61701060)supported by the National Natural Science Foundation of China。
文摘Visual background extraction algorithm(ViBe)uses the first frame image to initialize the background model,which can easily introduce the“ghost”.Because ViBe uses the fixed segmentation threshold to achieve the foreground and background segmentation,the detection results in many false detections for the highly dynamic background.To solve these problems,an improved ghost suppression and adaptive Visual Background Extraction algorithm is proposed in this paper.Firstly,with the pixel’s temporal and spatial information,the historical pixels of a certain combination are used to initialize the background model in the odd frames of the video sequence.Secondly,the background sample set combined with the neighborhood pixels are used to determine a complex degree of the background,to acquire the adaptive segmentation threshold.Thirdly,the update rate is adjusted based on the complexity of the background.Finally,the detected result goes through a post-processing to achieve better detection results.The experimental results show that the improved algorithm will not only quickly suppress the“ghost”,but also have a better detection in a complex dynamic background.
文摘Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.
基金supported by the National Natural SciencFoundation of China(Nos.U1636125,61601027)
文摘For the performance issues of satellite transceivers suffering passive intermodulation interference,a novel and effective digital suppression algorithm is presented in this paper.In contrast to analog approaches,digital passive intermodulation（PIM） suppression approaches can be easily reconfigured and therefore are highly attractive for future satellite communication systems.A simplified model of nonlinear distortion from passive microwave devices is established in consideration of the memory effect.The multiple high-order PIM products falling into the receiving band can be described as a bilinear predictor function.A suppression algorithm based on a bilinear polynomial decorrelated adaptive filter is proposed for baseband digital signal processing.In consideration of the time-varying characteristics of passive intermodulation,this algorithm can achieve the rapidness of online interference estimation and low complexity with less consumption of resources.Numerical simulation results show that the algorithm can effectively compensate the passive intermodulation interference,and achieve a high signal-to-interference ratio gain.
基金Project(61071162) supported by the National Natural Science Foundation of China
文摘In order to improve image quality, a novel Retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information in the intensity image to estimate the illumination. After locating the points, the whole illumination image was computed by an interpolation technique. When attempting to recover the reflectance image, an adaptive method which can be considered as an optimization problem was employed to suppress noise in dark environments and keep details in other areas. For color images, it was taken in the band of each channel separately. Experimental results demonstrate that the proposed algorithm is superior to the traditional Retinex algorithms in image entropy.
基金supported by the Natural Science Foundation of China (U22A20214)。
文摘Active Magnetic Bearing(AMB) is a kind of electromagnetic support that makes the rotor movement frictionless and can suppress rotor vibration by controlling the magnetic force. The most common approach to restrain the rotor vibration in AMBs is to adopt a notch filter or adaptive filter in the AMB controller. However, these methods cannot obtain the precise amplitude and phase of the compensation current. Thus, they are not so effective in terms of suppressing the vibrations of the fundamental and other harmonic orders over the whole speed range. To improve the vibration suppression performance of AMBs,an adaptive filter based on Least Mean Square(LMS) is applied to extract the vibration signals from the rotor displacement signal. An Iterative Search Algorithm(ISA) is proposed in this paper to obtain the corresponding relationship between the compensation current and vibration signals. The ISA is responsible for searching the compensating amplitude and shifting phase online for the LMS filter, enabling the AMB controller to generate the corresponding compensation force for vibration suppression. The results of ISA are recorded to suppress vibration using the Look-Up Table(LUT) in variable speed range. Comprehensive simulations and experimental validations are carried out in fixed and variable speed range, and the results demonstrate that by employing the ISA, vibrations of the fundamental and other harmonic orders are suppressed effectively.
基金Supported by the National Nature Science Foundation of China(No.61302074)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20122301120004)+1 种基金the Natural Science Foundation of Heilongjiang Province(No.QC2013C061)Research Foundation of Education Bureau of Heilongjiang Province(No.12531480)
文摘The negative impact on communication performance in wireless multi-hop communication net-work caused by limited bandwidth,high bit eror rate （BER）,fading,noise and interference is alleviated by an adaptive filtering game based on frequency subbands selection and predetemined threshold.Such threshold is being obtained in Gaussian and multipath fading channel according to the frequency-matching principle and BER performance.The dynamic selection of subbands will obtain high use efficiency without the help of frequency hopping,and propound a new thought to improve band limited communication for wireless multi-hop communication network.The effectiveness of the adaptive filtering method has been verified by interleaving spread spectrum orthogonal frequency division multiplexing （ISS-OFDM） in different interference conditions,and the simulating results based on network simulator 2 （NS2） indicate that system BER can be improved greatly.
基金The National Natural Science Foundation of China(No.U19B2031).
文摘A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 62266030 and 61863025)。
文摘Regulation plays a pivotal role in mitigating the spread of rumors, serving as a vital tool for maintaining social stability and facilitating its evolution. A central challenge lies in establishing an effective regulatory framework despite limited resources available for combating rumor propagation. To address this challenge, this paper proposes a dynamic and adaptive regulatory system. First, based on observed regulatory patterns in real-world social networks, the rumor propagation process is divided into two distinct phases: regulation and intervention. Regulatory intensity is introduced as an indicator of user state transitions. Unlike traditional, non-adaptive regulatory models that allocate costs uniformly,the adaptive model facilitates flexible cost distribution through a manageable individual regulatory intensity. Moreover,by introducing adaptive strength, the two cost allocation models are integrated within a unified framework, leading to the development of a dynamic model for rumor suppression. Finally, simulation experiments on Barabási–Albert(BA)networks demonstrate that the adaptive regulatory mechanism significantly reduces both the scope and duration of rumor propagation. Furthermore, when traditional non-adaptive regulatory models show limited effectiveness, the adaptive model effectively curbs rumor propagation by optimizing cost allocation between regulatory and intervention processes, and by adjusting per-unit cost benefit differentials.
基金supported by the National Natural Science Foundation of China(31171082)the Natural Science Foundation of Anhui Province(070413138)+1 种基金the Key Research Foundation of the Anhui Provincial Education Department(KJ2009A167)the Foundation of Key Laboratories of Anhui Province and the Anhui Provincial Education Department
文摘The influence of intracortical inhibition on the response adaptation of visual cortical neurons remains in debate. To clarify this issue, in the present study the influence of surround suppression evoked through the local inhibitory interneurons on the adaptation effects of neurons in the primary visual cortex （V1） were observed. Moreover, the adaptations of V1 neurons to both the high-contrast visual stimuli presented in the classical receptive field （CRF） and to the costimulation presented in the CRF and the surrounding nonclassical receptive field （nCRF） were compared. The intensities of surround suppression were modulated with different sized grating stimuli. The results showed that the response adaptation of V1 neurons decreased significantly with the increase of surround suppression and this adaptation decrease was due to the reduction of the initial response of V1 neurons to visual stimuli. However, the plateau response during adaptation showed no significant changes. These findings indicate that the adaptation effects of V1 neurons may not be directly affected by surround suppression, but may be dynamically regulated by a negative feedback network and be finely adjusted by its initial spiking response to stimulus. This adaptive regulation is not only energy efficient for the central nervous system, but also beneficially acts to maintain the homeostasis of neuronal response to long-presenting visual signals.
基金supported by the National Natural Science Foundation of China(grant nos.T2225020 and 92254306 to W.J.,grant no.32027901 to T.X.,grants nos.92354307,91954201,31971289 to G.Y.,grant nos.32322050 and 32170704 to L.G.)the National Key Research and Development Program of China(grant nos.2022YFC3400600 and 2021YFA1301500 to W.J.)+2 种基金the National Science and Technology Innovation 2030 Major Program(grant no.2022ZD0211900 to L.G.)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(grant no.YSBR-104 to W.J.)The Strategic Priority Research Program of the Chinese Academy of Sciences(grant no.XDB37040104 to W.J.and grant no.XDB37040402 to G.Y.).
文摘In deep learning super-resolution microscopy,concerns exist about the generation of artifacts,and methods for artifact suppression are lacking.We developed a self-adaptive fine-tuning method that dynamically adjusts the parameters of the models to minimize the loss function,which includes direct quantification of artifacts from live-cell imaging.Integrating self-adaptive fine-tuning with super-resolution models enables significant arti-fact reduction in the visualization of nanoscale organelle interactions at high spatial-temporal resolution.
基金supported by the National Natural Science Foundation of China(No.41074080)the Important National Science&Technology Specific Projects(No.2011ZX05019-008)
文摘To improve the data quality of converted waves, and better identify and suppress the strong ground-roll interference in three-component （3C） seismic recordings on land, we present an adaptive polarization filtering method, which can effectively separate the ground- roll interference by combining complex polarization and instantaneous polarization analysis. The ground roll noise is characterized by elliptical plane polarization, strong energy, low apparent velocity, and low frequency. After low-pass filtering of the 3C data input within a given time-window of the ground roll, the complex covariance matrix is decomposed using the sliding time window with overlapping data and length that depends on the dominant ground-roll frequency. The ground-roll model is established using the main eigenvectors, and the ground roll is detected and identified using the instantaneous polarization area attributes and average energy constraints of the ground-roll zone. Finally, the ground roll is subtracted. The threshold of the method is stable and easy to select, and offers good ground- roll detection. The method is a robust polarization filtering method. Model calculations and actual data indicate that the method can effectively identify and attenuate ground roll while preserving the effective signals.
文摘One of the aerodynamic phenomena associated with high performance aircraft is the high frequency vortex induced buffeting. The buffeting load can lead to high cyclic strain and stress,dramatically reduce the fatigue life of composite structures. In this paper, piezoelectric patches are bonded on the surface of composite panel. The dynamic response of the structure is measured by using bonded piezoelectric sensors. Filtered adaptive control algorithm is used to control the strain of piezoelectric actuators actively, so as to increase the modal damping coefficient of the composite panel, suppress the dynamic response and improve the fatigue performance of the structure. The feasibility of this method is verified in model experiments.
基金National Nature Science FoundationNational Deferise Research Funds
文摘A convenient implementation approach to space-time adaptive processing for airborne radar has been proposed, which is added by some auxiliary array elements in the area of main-lobe clutter on the basis of 2-D Capon approach . It is of practical use for its small computational load. This approach possesses the ideal performance in the area of main-lobe clutter . In addition, the approach which is added by some auxiliary beams in the area of main-lobe clutter has also been discussed.
文摘In non-homogeneous environment, traditional space-time adaptive processing doesn＇t effectively suppress interference and detect target, because the secondary data don＇ t exactly reflect the statistical characteristic of the range cell under test. A ravel methodology utilizing the direct data domain approach to space-time adaptive processing （ STAP ） in airbome radar non-homogeneous environments is presented. The deterministic least squares adaptive signal processing technique operates on a ＂snapshot-by-snapshot＂ basis to dethrone the adaptive adaptive weights for nulling interferences and estimating signal of interest （SOI）. Furthermore, this approach eliminates the requirement for estimating the covariance through the data of neighboring range cell, which eliminates calculating the inverse of covariance, and can be implemented to operate in real-time. Simulation results illustrate the efficiency of interference suppression in non-homogeneous environment.
文摘A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.
