最新刊期
卷 44 ， 期 9 ， 2016
- 摘要：In the conventional beam-forming (CBF) under low signal to noise ratio (SNR),the spectrum values of each azimuth are accumulated by equal weight,and the spectrum values of targets are usually inundated in those of non-targets,so the underwater targets with unknown radiated noise can be hardly detected.In order to detect the effective target signal,a target detection method based on the beam domain phase stability is proposed.According to the feature that the underwater target radiates noise with stable line spectrum and the difference of the beam domain phase stability of each azimuth,this method cumulates spectrum values of each azimuth based on the beam domain phase variance by weighted statistical algorithm.Therefore,the azimuth of the underwater target is effectively estimated.The numerical simulation and experimental results both verify that,compared with the conventional beam-forming,this method can well enhance the energy of the target azimuth,restrain the background noise disturbances of non-target azimuth,and improve the SNR gain of the target detection.关键词：array signal processing;underwater target radiated noise;beam domain phase stability;weighted statistical;Target Detection390|1098|1更新时间：2025-07-16
- 摘要：Inconsistency often occurs during ontology evolution,and leads to the invalidity of standard reasoning.Minimal unsatisfiablility-preserving sub-TBox (MUPS) can provide an explanation of the unsatisfiability of a concept in an ontology.Finding all MUPS is an important nonstandard reasoning task in ontology engineering.Most of the approaches for calculating MUPS are built on external description logic reasoners.However,a reasoner-based method can hardly achieve positive efficiency and stability.In this paper,we propose a reasoner-independent approach to calculating MUPS using graph representation.We first transform DL ontologies to graphs,and find MUPS by computing the minimal unsatisfiability-preserving path-pair (MUPP) based on the transformed graphs.We implement and evaluate our approach.The experimental results demonstrate that our approach performs well in efficiency and stability.关键词：ontology;description logic;inconsistency handling;minimal unsatisfiablility-preserving sub-TBox434|427|2更新时间：2025-07-16
- 摘要：In the analysis of two-dimension diffraction gratings,rigorous coupled wave analysis (RCWA) takes a long time and a large computer memory.The perturbation method (PM) is combined with RCWA to enhance its computational speed for the analysis of two-dimension structures.In the analysis of the non-rectangular gratings,the grating is approximated by a stack of lamellar gratings.We obtain the eigenvalues of the reference layers by RCWA firstly,and then get the eigenvalues of the rest layers by PM.It shows that PM can shorten the calculation efficiency at the basis of achieving the calculation accuracy.For the simulation example,when the truncation order is 12,the calculation time saves 45%.关键词：gratings;perturbation method;diffraction;RCWA286|433|0更新时间：2025-07-16
- 摘要：The high peak to average power rate (PAPR) of orthogonal frequency division multiplexing (OFDM) signal reduced the efficiency of the high power amplifier (HPA),and led the OFDM signal suffered from nonlinear distortion caused by HPA and the bite error rate (BER) of the system became worse.This paper proposes a nonlinear distortion compensation method based on clipping and compressive sensing.The transmitter uses a clipping method to reduce the PAPR of OFDM signal;the receiver utilizes a modified method based on the inverse model of HPA to reduce the nonlinear distortion caused by the HPA,and applies compressive sensing (CS) on counteracting the distortion caused by clipping.Simulations show that the proposed method can not only reduce the PAPR of the OFDM signal significantly,but also improve the BER performance of the system promisingly.关键词：orthogonal frequency division multiplexing(OFDM);peak to average power ratio(PAPR);clipping;nonlinear distortion compensation;compressive sensing(CS)277|539|7更新时间：2025-07-16
- 摘要：In order to realize the relativistic backward wave oscillator(RBWO) permanent magnet packaging,simulation software Magic is used and based on the structure of the relativistic backward wave oscillator(RBWO) with low magnetic field of 0.5T,through adding a partially reflecting cavity at the end of the device's slow wave structure to reduce the effect of the quality of electron beam on the beam-wave conversion,that is,to reduce the effect of guiding magnetic field,so this paper realized the Ku band relativistic backward wave oscillator normal operation at 0.3T.When the electron beam is 600kV and the beam current is 7kA,the output microwave power of 740MW and the efficiency of 18% are obtained in the simulation software Magic.Although the efficiency of the RBWO at 0.3T is lower than that at 0.5T(25%),guiding magnetic field of 0.3T is easier to realize in engineering.Experiment on the miniaturization of pulse power source,when the diode is 580kV and the beam is 6.5kA,achieves output power of 600MW and the frequency of 13.10 GHz with the corresponding pulse width of 25ns.关键词：relativistic backward wave oscillator (RBWO);miniaturization;Ku-band154|398|1更新时间：2025-07-16
- 摘要：Link prediction and attribute inference are two important tasks in social network mining.Most of the previous studies treated link prediction and attribute inference as different problems and sought for solutions separately.However,according to the theory of homophily,there are intrinsic relations between links and attributes in social network.We propose the link and attribute inference based on community (LAIC) solution which utilizes the community structure to connect link prediction and attribute inference.LAIC employs users' attribute and community structure for link prediction,and takes advantage of link information to get the attributes of communities for attribute inference of users.LAIC is not only able to predict attributes and links simultaneously,but also promotes the precision of link prediction and attribute inference mutually through iterations.Experiments on two real datasets verify the effectiveness of LAIC.关键词：social network;link prediction;attribute inference;community structure366|519|1更新时间：2025-07-16
- 摘要：Most of the existing Weibo sentiment analysis focuses on monolingual corpus like Chinese.However,a mixed use of Chinese and English becomes a popular form of expression.To better capture the social attention on public events,this paper proposes a bilingual lexicon based multi-class semantic orientation analysis for bilingual microblogs.We compare our proposed methodologies with majority vote,support vector machine (SVM) and K-nearest neighbor (KNN) by using cosine similarity which are competitive baseline methods.The experimental results show that our proposed methods outperform the three approaches we mentioned in terms of the accuracy and F1 score.关键词：bilingual semantic orientation analysis;semi-supervised gaussian mixture model(Semi-GMM);Kullback-Leibler divergence;sentiment lexicon416|1307|16更新时间：2025-07-16
- 摘要：Multi-label classification is widely used in genetic classification,drug discovery and text classification.The existing multi-label classification algorithms usually select nodes randomly from the network as their training set.However,during multi-label classification,different nodes have different effects.Given the number of nodes in the training set,a different training sub-set can lead to different classification accuracy.Hence,we introduce the concept of seed nodes, the classification procedure starts from the seed nodes,and after continuous reasoning,the labels of other nodes are inferred in the network.We propose an SHDA algorithm (Nodes Selection of High Degree from Each Affiliation) in which the nodes of high degrees from each affiliation belonging to the network are selected and merged,and after processing,the seed nodes are obtained.Experiments on several real-world datasets demonstrate that taking seed nodes as the training set to classify multi-labeled data can improve the classification performance.412|1063|3更新时间：2025-07-16
- 摘要：In the RFID (Radio Frequency Identification,RFID) system,due to inflexibility of Q value adjustment and weaknesses of the idle slots and collision slots processing within Q algorithm of EPC C1G2 protocol,this paper proposes FSA(Framed-Slotted Aloha,FSA) anti-collision algorithm based on continuous slot prediction.The proposed algorithm analyzes the relationship between frame length and the number of tags in different continuous slots status based on Markov slot status model.Continuous slot prediction mechanism and adaptive hashing scheme are proposed to implement that the time slots in read phase are mostly success slots,which effectively reducing invalid slots occur.Simulation results show that the proposed algorithm can flexibly adjust the frame size,improve throughput and reduce transmission delay and overhead,which provides a reasonable solution to integrity problems of massive data in the IoT (Internet of Things,IoT).关键词：radio frequency identification (RFID);anti-collision algorithm;Aloha;slot prediction315|424|6更新时间：2025-07-16
- 摘要：With a dual word,we can reconstruct the feedback polynomial of a linear scrambler when the synchronization is complete.An eavesdropper must achieve synchronization before recovering scrambler.Based on the algorithm of reconstruction of linear scrambler,we present techniques to achieve blind synchronization.We can get a set of multiples of the feedback polynomial when course synchronization is complete.Meantime,we can also recover the feedback polynomial and a scrambler sequence.Then,we need architecture of frame to achieve fine synchronization with the descrambled data.The study is based on the assumption that the channel is noiseless and then extended to the noisy channel condition.In order to reduce the computational complexity,we also propose a normal scheme to compute the statistic on the base of Walsh-Hadamard transformation.关键词：dual word;frame synchronous scrambler;linear feedback shift register (LFSR);blind synchronization;Walsh-Hadamard transformation160|466|7更新时间：2025-07-16
- 摘要：The channel state information (CSI) at base station (BS),obtained from users in the multiuser multiple input multiple output (MU-MIMO) system,leads to precoding performance degradation in frequency division duplexing (FDD) system.Existing robust beamforming precoding algorithms in MU-MIMO can reduce the performance loss caused by imperfect CSI.However,these algorithms only take one or two robustness channel errors into consideration,as a consequence,the system performance is limited to be improved.By establishing joint channel error model including channel estimation error,quantization error and delay error,we derive the closed-form solution of robust beamforming matrix based on minimum mean square error (MMSE).And then,we derive the closed-form solution of robust beamforming matrix based on MMSE of signal leakage with distributed characteristics while applying to distributed communication system.When compared to the traditional MMSE algorithm which only considers quantization error,numerical analysis shows that,the proposed centralized and distributed downlink MU-MIMO beamforming algorithms have better sum rate and bit error rate (BER),and reduce the precoding performance loss caused by the above three channel errors.关键词：multiuser multiple input multiple output;channel state information;frequency division duplexing;channel error;beamforming;minimum mean square error441|434|2更新时间：2025-07-16
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Research on the Phase Error Compensation in Synthetic Aperture Ladar by Using Optimization Algorithm
摘要：In the field of remote sensing,the platform vibration is one of the important problems of synthetic aperture ladar(SAL).There is no efficient method in compensating the platform vibration of SAL currently.The platform vibration effects the phase of the received data.By analyzing the mechanism of platform vibration,the phase error caused by platform vibration can be described by polynomial function.The vibration is compensated by optimization algorithm which optimizes the polynomial coefficients based on this conversion model.In optimization process,proper object function is needed and the phase of received data is compensated by optimization result,then the compensated data is compressed by matched filter.By simulation and experimental result,the conclusion is the better result of compression can be achieved after compensate the phase error by using the optimization algorithm.The research has offered candidate technology to platform vibration compensation.关键词：remote sensing;phase error;vibration compensation;optimization algorithm;polynomial135|322|2更新时间：2025-07-16 - 摘要：To overcome the shortcoming of the load balancing method in cloud computing,a load balancing method for cloud computing platform is proposed,which is inspired by the system logic hierarchical and multi-agent theory.By making use of the idea of logical layer of cloud computing platform,on the one hand,task monitoring agents and task sub-agents are set up in the task agent layer.According to the diversity of users' tasks,the method completes the task scheduling based on the task priority and QoS constrained;on the other hand,resource monitoring agents and resource sub-agents are set up in resource agent layer.Considering the heterogeneity of physical nodes,the method maps the virtual machine to the physical nodes by the resource allocation policy based on the greedy heuristic.Implementation results show that the new method outperforms the others in terms of efficiency of task scheduling,makespan of task,task time-constraint violation time and load balancing.Moreover,after multi-agent effectively shares the management load of the center management node,task processing ability,resource utilization rate and robustness of the cloud computing platform are significantly improved.关键词：load balancing;cloud computing platform;hierarchy;multi-agent296|582|7更新时间：2025-07-16
- 摘要：Community detection method is significant to character statistics of complex network.Community detection in inhomogeneous structured network is an attractive research problem while most previous approaches attempted to divide networks into communities which are based on node or edge measurement.The label propagation algorithm (LPA) adopts semi-supervised machine learning and implemented community detection in an intelligent way with automatic convergent process of network node label iteration but it often results in low efficiency in the final convergent process.In this article,aiming to promote low efficiency and stagnant converging rate of LPA in network with overlapping communities,we propose a new method (ESLPA) for community detection using epidemic spreading model combined with network connection matrix's largest Eigenvalue as label propagation threshold.Extensive experiments in synthetic signed network and real-life large networks derived from online social media are conducted to explore optimal mechanism of the most suitable community detecting virus infection threshold.Experiments result prove that our method is more accurate and faster than several traditional modularity based community detection methods such as COPRA,GN,FastGN and CPM.关键词：overlapping community detection;Epidemic model;information spreading;largest eigenvalue314|569|0更新时间：2025-07-16
- 摘要：A prediction algorithm of the secondary factor for automatic identification system (AIS) signal propagation is studied.The reflection coefficient on AIS band given is derived based on the in-depth study of the effects for sea surface parameters on the secondary factor of AIS signal.The secondary factor of AIS signal in the different sea states is given under the influence of the sea temperature,salinity,the height of antennas and the length of propagation distance.The results will contribute to the high-precision measurement of the propagation delay for AIS signal along the sea.关键词：AIS signal propagation;secondary factor;prediction algorithm;ranging precision197|433|1更新时间：2025-07-16
- 摘要：Moving object detection under complex-background is always a challenging issue,and in order to defend these challenges,this paper proposed an algorithm named MMBM (Moving object detection based on Multi-layer Background Model).First,samples are selected from neighbors of each pixel of the first frame to initialize background model.Only one frame image is needed for initialization.Second,in order to update the background model adaptively,random sampling technique is introduced,i.e.,selecting one code word randomly from the background model and then updating it with new background pixel,which overcomes the deficiency of the wrong classified code word overstaying in the background model.Multi-layer background model is proposed in order to overcome the influence of multi-disturbance in dynamic background,in which one pixel is tested through multi-layers,so as to guarantee and improve the accuracy of background pixels.Finally,Experimental results show that this algorithm can overcome the influence of multi-disturbance existing in dynamic outside scenes effectively,and at the same time,achieve a higher detection rate and recognition rate over the existing classical algorithms.关键词：dynamic background;object detection;random sampling;video surveillance;pixel classifier206|1214|2更新时间：2025-07-16
- 摘要：There are three different MPPT architectures in photovoltaic system:central,grouped and distributed architecture,and their power generation efficiencies are researched respectively.The simulation results show that the annual generation capacity of photovoltaic system with distributed MPPT architecture can be increased up to 4.65%~19.62% compared to system with central MPPT,and 2.64%~12.86% compared to system with grouped MPPT.The actual efficiency increasement varies with the proportion of time partial shading and the degree of module parameter mismatch,and is independent of specific shadow mode respectively关键词：MPPT architectures;photovoltaic system;power generation efficiency;partial shading;module parameter mismatch168|351|3更新时间：2025-07-16
- 摘要：This paper presents a markerless facial expression capture and reproduce algorithm.Firstly,an uniform mesh model is built based on the feature points from ASM(Active Shape Model).It can cover 85 percent of the face.Then,a method to capture facial expression based on the face model is proposed.The optical flow tracking is used to track the feature points with particle filter for stablizing the result.The feature points' displacement can drive the overall mesh to deform as the initial value of the mesh tracking.Finally,the captured expression data is used to drive face models with different methods for the models of different dimensions,and then the facial animation can be reconstructed.Experimental results show that the proposed algorithm can capture facial expressions well,and the animation effect is good when mapping the captured expression to 2D cartoon or 3D virtual face models.关键词：marker-less tracking;facial expression capture;facial animation reconstruction202|1144|3更新时间：2025-07-16
- 摘要：In order to realize unambiguous multi-target range and velocity measurement in FMCW (Frequency Modulation Continuous Wave) radar,a trapezoid waveform modulation is proposed and its worst-case matching numbers is derived.Then two processing algorithm,TFBM and FGTC,and their matching condition have been innovatively designed.TFBM (Tolerance-Fast Beat frequency Matching) algorithm can quickly find all possible results for each period.FGTC (Fast Ghost Targets Canceling) algorithm can quickly eliminate the ghost targets which are caused by TFBM algorithm.Strictly theoretical derivation and simulation results show that the joint use of TFBM and FTGC algorithm on trapezoid waveform radar can not only measure multi-target range and velocity without ambiguity,but also reduce the computational complexity significantly.关键词：FMCW;trapezoid waveform modulation;multi-target measurement;range-velocity decoupling;fast pairing algorithm177|1186|6更新时间：2025-07-16
- 摘要：Since the existing cluster cooperative routing algorithms select cluster heads without considering the characteristics of cooperative communication and don't balance the cluster member according to the capacity of cluster heads,they can't fully exploit the advantage of cooperative communication on saving energy consumption.A cluster cooperative routing algorithm based on evolutionary game (CCREG) is proposed.Firstly,the energy of virtual node is the metric of cluster head selection.Secondly,the model of cluster membership based on the evolutionary game is formulated,where member nodes select different clusters to join in leading to different payoffs which are decided by the capacity of the cluster head and the number of cluster members.Each member node selects a cluster to join in,till it can't achieve more payoffs by changing the cluster to join in.The experiment shows that CCREG can prompt the network lifetime by 14%~70% with two cluster headers,by 5%~80% with three cluster headers,compared with cooperative multi-input multi-output routing (CMIMO).关键词：cooperative routing;the evolutionary game;cluster routing;network lifetime132|848|5更新时间：2025-07-16
- 摘要：Functional materials infiltrated photonic crystal fibers are optical devices that are wavelength tunable,all in fiber structure and easy to be integrated into optical systems,and have been a prominent research focus in optical fiber photonic devices.A highly sensitive strain sensor is made by selectively infiltrating high refractive index matching liquid into the air holes adjacent to the fiber core of a hollow core photonic crystal fiber (PCF) by capillary force,and splicing single mode fibers at both ends of the PCF.A strain sensitivity of 4.36pm/με is obtained by a device with infiltration length of 30mm and liquid refractive index of 1.508.The experimental results agree well with the simulation predictions.Such a device can be used for strain sensing with high sensitivity.关键词：fiber optics;photonic crystal fiber;selective infiltration;strain measurement115|413|1更新时间：2025-07-16
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Optimal Design of Sparse Reconfigurable Antenna Array Based on Multitask Bayesian Compressed Sensing
摘要：In light of the equivalent joint sparse learning model,an effective method based on multitask Bayesian compressed sensing (MT-BCS) is presented for the design of pattern reconfigurable antenna arrays.The method can dynamically reconfigure arbitrary radiation patterns with the exact pattern details and as fewer number of antenna elements as possible.Firstly,the sparse learning model of multiple reference patterns is built based on MT-BCS theory and priori assumption about the priori probability of weight vectors.Then fast relevance vector machine (RVM) is exploited to estimate maximum posterior probability of hyper-parameter and further to obtain array optimizing positions and excitations.By varying excitations and optimized element positions,different patterns with desired and precise particulars can be achieved.Simulation results validate the efficiency of the proposed method for the design of maximally sparse reconfigurable antenna.关键词：sparse array;pattern reconfigurable antenna;multitask Bayesian compressed sensing;relevance vector machine116|709|1更新时间：2025-07-16 - 摘要：In single blind motion deblurring,salient edges have been the key to success of kernel estimation.To this end,a new blind motion deblurring algorithm is proposed based on optimal reweighted L1 norm.Firstly,the weighted L1 based blind kernel estimation model is constructed.Then,for reducing the influence of noise and tiny structures,an image smoothing model is introduced into the optimal estimation of weights.A numerical algorithm based on iterative shrinkage-thresholding is also proposed to solve the blind kernel estimation model.At last,a fast non-blind deconvolution method using Hyper-Laplacian priors is utilized to restore the final image.Experimental results on simulated and real-world data demonstrate the superiority of the proposed method.关键词：blind image deblurring;weighted L1 norm;iterative shrinkage-thresholding159|639|0更新时间：2025-07-16
- 摘要：The synonymy and ambiguity of visual words always exist in the conventional bag of visual words model based object classification methods.Besides,the noisy visual words,so-called "visual stop-words" will degrade the semantic resolution of visual dictionary.In this article,an image object classification method with homoionym based adaptive soft-assignment and chi-square model is proposed to solve these problems.Firstly,PLSA (Probabilistic Latent Semantic Analysis) is used to analyze the semantic co-occurrence probability of visual words,excavate the latent semantic topics in images,and get the latent topic distributions induced by the words; Secondly,the KL divergence is adopted for measuring semantic distance between visual words,which can get semantically related homoionym; then,adaptive soft-assignment is proposed to realize the soft mapping between SIFT features and some homoionym; finally,the Chi-square model is introduced to eliminate the "visual stop-words" and reconstruct the visual vocabulary histograms,and moreover,SVM (Support Vector Machine) is used to accomplish object classification.Experimental results indicated that the adverse effects produced by the synonymy and ambiguity of visual words can be overcome effectively,the distinguishability of visual semantic resolution is improved,and the image classification performance is substantially boosted compared with the traditional methods.关键词：bag of visual words model;probabilistic latent semantic analysis;K-L divergence;Chi-square model;object classification125|353|0更新时间：2025-07-16
- 摘要：For network with nodes joining and leaving dynamically,a topology inference algorithm based on maximum common path matching is proposed.In this algorithm,in order to improve the estimating precision of similarity metric,two small packets of sandwich probes are rearranged in accordance with cross-traffic effects,and the similarity metric is estimated according to the new rearranged sandwich probes.The new joined nodes are directly added into the existing topology by matching the length of common path.By using the information of TTL hop count to select match path,the efficiency of topology inference is improved.The simulating results show that this algorithm can effectively improve the accuracy and efficiency of topology inference.关键词：network measurement;network tomography;topology inference;maximum common path matching115|423|0更新时间：2025-07-16
- 摘要：Data center networks leverage multiple parallel paths connecting end host pairs to offer high bisection bandwidth forcluster computing applications.However,state of the art flow scheduling algorithms may cause unfair link utilization and saturation of core switches,resulting in overall bandwidth loss.In the paper,we regard the flow scheduling problem as a 0-K knapsack problem and propose a new flow scheduling algorithm named DPSOFS based on DPSO.DPSOFS formulates the position,velocity and their operation rules of particles according to Fat-Tree topology structure,and defines objective function as the difference of the number of conflict flows between two iterations.Moreover,our proposed mechanism reduces random search blindness by limiting the range of the path search.The simulation suggests that it can improve overall network bisection efficiently.关键词：Fat-Tree;data center network;DPSO;flow scheduling142|599|11更新时间：2025-07-16
- 摘要：The auditory quality of wideband audio is generally degraded due to the lack of the high-frequency in network transmission,so this paper presents a kind of audio bandwidth extension method from wideband to super wideband based on local least square support vector machine.In the light of the nonlinearity of audio spectrum,the high-frequency fine spectrum of audio signals is predicted by using phase space reconstruction and local least square support vector machine.Combining with the estimation of high-frequency sub-band energy based on Gaussian mixture model,the proposed method can effectively recover the high-frequency components in the frequency range 7kHz~14kHz through the envelope adjustment of high-frequency spectrum at last.Subjective and objective testing results indicate that the proposed method improves the auditory quality of wideband audio and outperforms the reference methods of audio bandwidth extension.关键词：audio coding;bandwidth extension;Gaussian mixture model;local least square support vector machine107|497|2更新时间：2025-07-16
- 摘要：As an important data acquisition technology,throughput of RFID system affects performance of the data acquisition terminal of Internet of Things directly,but the throughputs of passive RFID system anti-collision algorithms of framed slot are generally low.Two factors influencing throughput of RFID systems are analyzed,which were frame length and the way of solving collided slots.Mathematical models of frame adjusting and tag collision are set up and solved,and then a solution is proposed for optimizing the anti-collision ALOHA algorithms of framed slot,that is,frame length adjusting adaptively and collision binary splitting timely.On these bases,the adaptive binary splitting frame slotted ALOHA anti-collision is constructed.The simulation results show that ABSFSA algorithm is able to decrease the invalid slots effectively in the same condition,and the throughput of RFID system is steadily improved to 45% obviously.The research work provides a referable mathematical model for optimizing the anti-collision ALOHA algorithms of framed slot,and a valuable solution for improving performance of data acquisition terminal of Internet of Things.关键词：RFID;ALOHA anti-collision algorithm;frame length adjusting adaptively;binary splitting mechanism;tag estimation function130|391|2更新时间：2025-07-16
- 摘要：The traditional method based on probabilistic transfer matrices (PTM) enables accurate evaluation of reliability for moderately large combinational circuits,but it can only be applied to combinational circuits.Flip-flop is an important component of sequential circuits,and its reliability estimation is essential for reliability analysis of sequential circuits.Therefore,a general computational framework for reliability estimation of flip-flops based on PTM (F-PTM) and a decision theorem of circuit's PTM are proposed.Firstly,a logical function of the flip-flop circuit is expressed;and then its PTM is calculated by deduction employing the proposed decision theorem;finally,the circuit's reliability is estimated by probability distribution of its inputs.Compared with the traditional PTM method,the F-PTM method can calculate PTMs for both combinational circuits and flip-flop circuits.Experimental results of the classical flip-flop circuits and 74X series circuits show that the F-PTM method is efficient and feasible.The comparison of our method with multiple-pass method and Monte Carlo simulation also demonstrate that the reliability results estimated by the F-PTM method is more accurate.关键词：soft error;flip-flop;reliability estimation;probabilistic transfer matrix;semi-tensor product74|385|0更新时间：2025-07-16
- 摘要：In order to overcome the problem that the topology performance optimization of wireless sensor network is single,an indicator which can represent the bi-directional communication quality of a link is defined.Then the link communication quality,node interference and balance of surplus energy are integrated into the utility function.Finally,a self-maintaining topology control game algorithm based on link quality (SMGLQ) is proposed.The theoretical analysis proves that SMGLQ algorithm can converge to a Pareto optimal.Simulation results show that SMGLQ chooses the links with better communication quality for the network.Moreover,it can reduce the energy consumption.关键词：wireless sensor network (WSN);topology control;link quality;game theory117|343|3更新时间：2025-07-16
- 摘要：Visual attention is one of the research hotspots in the field of machine vision,which is positive significance for development of target detection and target tracking.This paper presents a particle filter based visual attention model that is applied to detect moving target.Firstly,according to Bayes estimation theory,the method of particle weight calculation is established by visual bidirectional (Top-Down/Bottom-Up) fusion attention.Then motion attention and target color attention are adopted as input of the attention model,and moving target saliency is calculated through the importance sampling,particle weight calculation,resampling and particle saliency map processing.Lastly,the target position is determined by distribution of particle.Different video complex scene test results show that this method is more effective and accurate than the traditional method for detection of moving target.关键词：motion attention model;moving target detection;particle filtering;fusion134|408|3更新时间：2025-07-16
- 摘要：A heuristic intelligent path planning method based on the multivariant optimization algorithm and the Bezier curve is presented.The path planning problem is transformed into an optimization problem through using the Bezier curve to represent a path in this method.Then,the multivariant optimization algorithm is applied to find the optimal control points of the best Bezier curve,aiming at finding the optimal path.The multivariant optimization algorithm searches the solution space through iterations of alternative global and local search.According to the different responsibilities,the search individuals (atoms) could be divided into two types:the global atoms and the local atoms.In each iteration,global atoms explore the whole solution space to local potential areas,and then,local atoms exploit each potential area.Obviously,atoms are characterized by multivariant responsibilities,hence the name of the multivariant optimization algorithm.The good performance of the multivariant optimization algorithm is ensured by the efficient communication and cooperation of multivariant atoms.To evaluate the performance of the multivariant optimization algorithm,comparative experiments against the other three classical heuristic path planning algorithms are carried out based on a standard testing map.The results show that our proposed method is superior to the other methods in optimality,stability and efficiency.关键词：multivariant optimization algorithm;global atom;local atom;path planning;Bezier curve95|913|8更新时间：2025-07-16
- 摘要：Remote sensing classification aims at extracting available geographic information from image spectrum for resources and environment monitoring,but due to the spectral drift effect,the lack of effective strategies on historical sample reuse for image processing technology based on pattern classification restricts remote sensing classification accuracy with limited target samples.To solve this problem,this paper proposes a transfer learning algorithm for remote sensing classification using improved Bayesian ARTMAP neural network.More productive resonance matching is used to suppress the unattractive property of category proliferation,so that the incremental expectation maximization can be introduced to update parameters adaptively.The classification prior knowledge of the historical samples is transferred to the target model.The experimental results show that this method can effectively compensate for the lack of target training data by reusing the historical samples and significantly improve the accuracy of remote sensing image classification compared with other sample utilization strategy.关键词：remote sensing classification;information extraction;transfer learning;ARTMAP;neural network263|710|2更新时间：2025-07-16
- 摘要：In order to improve the efficiency of test data generation for path coverage,a method for generating test data was proposed,which was based on automatic division of path and artificial fish-swarm (AFS) algorithm.Firstly,the relations between variables and nodes,and between variables and paths,were analyzed.Based on the analysis an algorithm for automatic division of path was presented,which can automatically judge the impact of variables on sub-paths.Secondly,an improved AFS algorithm was developed based on Levy flying and conjugate gradient.By making use of the result of path division and the improved AFS algorithm,a new method for searching test data was proposed.If there exist sub paths that the fish pass through in the process of using AFS to generate test data,the corresponding component of these fish were fixed,so that search space were reduced.Finally,the proposed method was applied to the test data generation of programs.It is shown that our method outperforms the related methods in running time,success rate and stability.关键词：software testing;path division;test data;path coverage;artificial fish-swarm algorithm107|348|4更新时间：2025-07-16
- 摘要：Semantics-based recommendation technology has recently received a lot of attention in information services community.Compared with traditional recommendation algorithms,semantics-based recommendation algorithms have the marked advantages in the aspects of real-timing,robustness and recommendation quality.From the status and progress of domestic and foreign research,we summarize the following four aspects:semantics-based content recommendation algorithms,semantics-based collaborative filtering recommendation algorithms,semantics-based hybrid recommendation algorithms,and semantics-based social recommendation algorithms.And this paper is expected to provide a worthwhile reference for relevant researchers by detailedly analyzing semantics-based recommendation algorithms.Finally,we show readers the challenges and future research directions in this field.关键词：semantics;recommendation algorithm;content recommendation;collaborative filtering recommendation;hybrid recommendation;social recommendation185|1344|5更新时间：2025-07-16
- 摘要：By analyzing the constitution of the optimal adaptive weight,we find that the optimal adaptive weight only lies in a low-dimension subspace spanned by the desired signal steering vector and the interferences subspace.Generally,the number of interferences designed to suppress is much smaller than that of the array sensors.Consequently,once the interference-plus-signal subspace (IPSS) is estimated,only a low-dimension combination vector is needed to compute,which leads to a reduction of the computation complexity.First,we construct a complete IPSS.And then the sparse constraint is imposed on the combination vector to select the least number of column vectors of the complete IPSS to form the adaptive weight.Simulation results validate the effectiveness and robustness of the proposed algorithm.关键词：robust beamforming;sparse constraint;steering vector mismatch;regularization;convex programming195|485|6更新时间：2025-07-16
- 摘要：This paper proposes a structured Gaussian mixture model with constraint conditions (C-SGMM) for non-parallel corpora voice conversion.A small number of voice signals with the same syllables from the source and target non-parallel corpus are extracted as constraint conditions,then the correspondence between acoustic features of source and target corpus formed by these syllables are applied in the process of statistical acoustic model training.The constraint conditions are used to restrict the cluster centers of K-means clustering process,and they are also used in EM algorithm to adjust the voice frame's posterior probability belonging to a Gaussian distribution component for model training.Then Gaussian distributions in source and target structured Gaussian mixture models are aligned using acoustic universal structure principle and the conversion function can be derived.Results of both subjective and objective experiments indicate that the conversion performance obtained by the proposed method are advanced to that of the traditional structured method in cepstrum distortion,target tendency and speech quality aspects.The average cepstrum distortion of converted speech is only 0.52,the speaker recognition rate of the converted speech reaches 95.25%,and the performance closer to the conventional parallel corpora GMM based method is achieved.关键词：voice conversion;structure Gaussian mixture model;non-parallel corpora;constraint conditions103|685|3更新时间：2025-07-16
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