摘要:Online multi-target tracking is one of the key problems in video surveillance.According to the increasing need of smart monitoring,an online multiple target tracking algorithm based on fuzzy spatio-temporal cues was proposed.The fuzzy spatio-temporal multiple features were introduced to define the distance function,and the fuzzy c-means algorithm was adopted to derive the cross fuzzy membership degree matrix which was used to deal with the data association between the targets and the observations.To reduce the wrong initializations of the targets,an occlusion measurement about the levels of occlusion was defined according to the spatio-temporal cues.The new targets were discriminated from the false alarms by the occlusion measurement,and their corresponding tracks were initialized.Experimental results show that the proposed algorithm can accurately estimate the trajectories of multiple targets.The proposed algorithm can be applied in video surveillance,security,autonomous driving,etc.
摘要:In the spatial acoustic signal processing,for the issue of dimensionality mismatch between 2-dimensional (2D) sound field synthesis and practical sound source,and the issue of near-field distortion in the near-field sound source synthesis,this paper presents a 2.5-dimensional (2.5D) sound field synthesis method and a modified Wiener filter method for near-field compensation.The 2.5D sound field synthesis is achieved using the spherical harmonics expansion of higher order ambisonics (HOA).The modified Wiener filter is used to compensate the near-field distortion which arises when HOA is utilized to reproduce a 2.5D near-field sound source.Based on the concept of continuous loudspeaker array hypothesis,a general expression of the loudspeaker driving signal is derived.The experiments show that the proposed method reduced the relative error of the synthesized 2.5D near-field from 0.23 to 0.031 in comparison with the cosine regularization method.Meanwhile,the proposed method provides a larger effective listening area compared with the high-pass filter method.
关键词:acoustic signal processing;sound field synthesis;loudspeaker array;spherical harmonics
摘要:Calibrating camera is essential for intelligent surveillance systems.Conventional calibrating methods usually calibrate the target cameras one by one and can not handle non-overlapping cases or camera motion/disturbance.In this work,we present an interactive calibration framework based on 3D reconstruction.The reconstructed 3D feature point cloud is treated as the interface between the 3D background model and the target camera.Through 2D-3D matching,a target camera could be automatically calibrated against the 3D feature point cloud.Due to the matching is performed between the target image and the point cloud,non-overlapping cases can be well handled.Also,an online relative pose transfer scheme is proposed to deal with the problem of camera disturbance or motion efficiently.Experiments demonstrate the effectiveness of the proposed framework.
关键词:3D surveillance system;camera calibration;3D reconstruction;PTZ camera
摘要:The existing image segmentation models have problems of being sensitive to initialization information,slower segmentation and leaked weak image boundary regions.This paper presents a hybrid fast segmentation model which utilizes the local statistics of bias field approximated images,the global information of compatibility and the distance regularization method.Then the model is embedded into level set framework.In addition,a dual termination standard is constructed to improve the speed of segmentation.Experiments on synthetic and real images are conducted to verify the efficiency of our model.Moreover,comparisons with the well-known CV model,nonlinear adaptive level set model and region scalable fitting model demonstrate that the proposed model reduces the sensitivity to the initialization and improves the segmentation speed by 3~5 times.
摘要:The hardware implementation of lossless data compression is wildly used in big data computing and communication,since it combines the speed and power advantage of the dedicated circuit.This paper proposed a hardware compression circuit based on GNUzip(Gzip)lossless data compression algorithm.The dual Hash functions,parallel match processing,hardware storage oriented LZ77 compression data format and high-performance data adaptor were involved to accelerate the compression speed with the advantages of parallel calculation and pipeline structure.The hardware compression circuit,based on Verilog HDL,was tested and verified by field programmable gate array(FPGA).The test data shows that,compared with software implementation,the compression speed of hardware circuit is improved significantly while the compression rate is 65.9%.The average speed is up to 171Mb/s that can satisfy the real-time compression requests of network communication and data storage.
摘要:To suppress end effects of signal processing and judgment contingency of pattern recognition in the rotating machinery fault diagnosis method,an intelligent fault diagnosis method is proposed based on the cross-correlation matching endpoint extension local characteristic scale decomposition (CELCD) and the improved variable predictive model based class discriminate (VPMCD).Firstly,the characteristic of the decomposed signal is explored and the matched waveform is selected to complete the endpoint extension.Then the extension waveform is decomposed by the local characteristic scale decomposition (LCD),at the same time,and the intrinsic scale components (ISCs) with removed endpoint effect are obtained.Finally,the features of each ISC are extracted and input to the multi-model fusion-variable predictive model based class discriminate (MFVPMCD) classifier for the judgment of state probability.Experimental results show that the proposed method can effectively identify the running state of roller bearing.
关键词:cross-correlation matching endpoint extension;local characteristic scale decomposition (LCD);multi-model fusion;variable predictive model based class discriminate (VPMCD);fault diagnosis
摘要:Considering the features of the traditional Fuzzing technology,a method is proposed for Fuzzing test case generating in vulnerability exploiting,which is aimed at nonlinear solution and single input problem.This method takes advantage of the genetic algorithm and deals with those two problems mentioned above.The experiment results show that,the proposed solution has an obvious improvement compared with the early method which generates the test cases randomly.
摘要:This paper proposes a no-reference video quality assessment model by reducing the complexity of the human visual system(HVS).The characteristics of spatial domain and temporal domain of the videos are firstly extracted.Then multi-weight convergence is conducted by simulating visual perception according to different granularity from fine-grained to coarse-grained of video local block,video frame,video segment,etc.Finally the feature vector of the whole video is achieved.The support vector regression(SVR) is taken as quality assessment tool in this algorithm.The quality assessment of the unknown video is obtained without reference after supervised training.The experiments we have done show that the algorithm is not only superior to all of the other no-reference quality assessment algorithms,but also can be compared to part-reference algorithms.
摘要:In order to apply the data-driven technology in industry field,with the distillation column as one of the controlled objects,the hardware-in-the-loop simulation system is developed,and the data driven methods are applied to the process industry hardware-in-the-loop simulation system.Aiming at the huge computation and low efficiency of the dynamic principal component analysis method,an improved dynamic principal component analysis method is proposed,which remove the irrelevant variables or low relevant variables,reduce the amount of data,and improve the diagnostic efficiency by indiscernibility and the cross-degree.For the typical faults of the systems,the application result shows that the data-driven methods can detect the fault of hardware-in-the-loop simulation system,and compared with the traditional dynamic principal component,the simulation results show that the proposed method is more reliable with lower missing rate,and lower false rate,and in addition,it can detect the small process faults timely.
关键词:data driven;distillation column;hardware-in-the-loop simulation;dynamic principal component analysis (DPCA);indiscernibility
摘要:In the light of the motion type and characteristics of elderly people,we propose an approach which is based on triaxial accelerometer and hidden Markov model(HMM) for activities recognition.Firstly,we extract standard deviation(SD),energy,correlation coefficients,ratio forward(RAF),ratio vertical forward(RVF) as the features corresponding to different and similar activities of elderly people.Secondly,we define the activities recognition model based on HMM for elderly people.Finally,we use the Viterbi algorithm to recognize the activities for elderly people after the parameters are trained by Baum-Welch algorithm.The experimental results shows that our approach is can be applied for daily activity recognition of elderly people and the average recognition accuracy is 93.3%,specifically the accuracy of similar walking activities is 93.7%.
摘要:The track anomaly detection is the key issue to make sure flying anomaly detected in time for the route flight.Traditional probabilistic frameworks are always based on prior probabilities.Transferable belief model (TBM) theory can generalizes the Bayesian approach without prior probabilities and efficiently deal with heterogeneous data.However,the traditional TBM cannot deal with the discontinuity and uncertainty about the time.Considering the existence of unreliable evidence sources,an alternative anomaly detection method is proposed in the framework of transferable belief model (TBM) theory.A two-level architecture fusion system based on TBM is developed.The novelty of this work is that it can detect both unreliable evidence source and abnormal behavior of the targets within our architecture by using a temporal analysis and a new discounting coefficient through introducing the concept of contribution degrees of features.Detection of abnormal behavior is based on a prediction/observation process and the influence of the faulty sources is weakened through discounting coefficients.The simulations show the better accuracy of decision and precision of time compared with the dynamic evidence reasoning method.
关键词:Information fusion;track association;anomaly source data;decision theory
摘要:Source localization with an array is an important topic for wireless communication,radar,sonar,etc.In order to resolve the phase ambiguity in parameter estimation of a single high frequency near-field source with uniform circular array (UCA),a rotation-based algorithm is introduced to make the same sensor form virtual short base-line.First,a reference sensor is set at the center of UCA and its initial phase difference is utilized to compensate the measurements of other sensors,which are received before and after rotating UCA.Then,based on the phase difference of each sensor computed by correlation,the azimuth angle,elevation angle and range of the source can be estimated by least squares.Further,by using the obtained source parameters without ambiguity to eliminate the phase difference ambiguity of sensors with the longest base line before rotation,we can acquire more precise source parameters.Finally,the efficiency and performance of the method for a single high frequency source is verified by several simulations.
摘要:Compared to the conventional two-step localization method,the direct position determination (DPD) method has higher location accuracy.However,the DPD method is usually proposed for static target and is computationally expensive.This paper presents a novel DPD method for moving target at constant velocity based on the Doppler frequency shifts.First,the optimization model for directly determining the initial position and velocity of the emitter is constructed on the basis of maximum likelihood estimator (MLE),and the cost function is formulated as the maximal eigenvalue of the Hermitian matrix.In order to avoid multidimensional grid search,a Newton-type iterative algorithm based on matrix eigen-perturbation theory is proposed,which involves lower computational complexity than the multidimensional grid search.In addition,the compact Cramér-Rao bound (CRB) expressions for initial position,moving velocity and track estimates are derived,which can provide a theoretical prediction for target position determination.Simulation results corroborate that the estimate variance of the proposed method is able to attain the CRB with lower computational complexity.
摘要:In order to solve problems of high power consumption and low oscillation frequency in oscillator,this work presents a third-order quadrature oscillator circuit employing CDCTA (Current Differencing Cascaded Transconductance Amplifiers).The proposed structure employing only one CDCTA and three grounded passive capacitors realizes four explicit quadrature current outputs and two quadrature voltage outputs simultaneously.Meanwhile,the circuit power consumption is only 1.8mW,the maximum sensitivities value of only 0.5 and the oscillation frequency of up 10MHz magnitude.Moreover,its oscillation condition and oscillation frequency can be tuned electronically and independently.Results from computer simulation and hardware experiment validated the theoretical analysis of the circuit.
关键词:integrated circuit;low power consumption;oscillator;current differencing cascaded transconductance amplifiers (CDCTA);oscillation frequency
摘要:Workflow satisfiability(WS)is an essential claim to access control(AC)policies from the view of resource allocation.So far,the related researches are concentrated on the decision problem of WS,which finds a single solution to show the correctness of an AC policy.However,to further verify its rationality under resource exception,and to count all the solutions will be more useful.In this paper,the counting problem of WS with exclusion and binding constraints is addressed.The problem is proved to be #P complete by constructing a polynomial time counting reduction from the well-known #P complete problem of #3SAT to it,and then gets a theoretical basis to be solved appropriately.
摘要:In order to solve the problems about identity authentication,privacy protection,dynamic shared-key updating and de-synchronization that emerged in mobile radio frequency identification (RFID) authentication protocols,the paper proposes a mutual authentication protocol of mobile RFID whose shared-key can be updated dynamically.Based on Hash cryptography,the proposed protocol uses pseudo-random number to perform simultaneous operations on secure shared-key updating and identity authenticating,then uses a method of dynamic deletion and addition of shared-key that respectively stored in current data table and historic data table to reserve the coherency of shared-key among backend server,reader and tag after the latest legal authentication.The securities and efficiencies analysis show that the protocol can achieve secure updates of dynamic shared-key,identity authentication and shared-key synchronization after being attacked,and in addition,the proposed protocol has strong computation and storage abilities.Compared with other similar mobile RFID protocols,the proposed protocol can make up for the deficiency of these protocols,which is suitable for RFID systems with a large number of passive tags.
关键词:radio frequency identification (RFID);mobile;authentication protocol;dynamic shared-key
摘要:Current face recognition algorithms use hand-crafted features or extract features by deep learning.This paper presents a face recognition algorithm based on improved deep networks that can automatically extract the discriminative features of the target more accurately.Firstly,this algorithm uses ZCA(Zero-mean Component Analysis)whitening to preprocess the input images in order to reduce the correlation between features and the complexity of the training networks.Then,it organically combines convolution,pooling and stacked sparse autoencoder to get a deep network feature extractor.The convolution kernels are achieved through a separate unsupervised learning model.The improved deep networks get an automatic deep feature extractor through preliminary training and fine-tuning.Finally,the softmax regression model is used to classify the extracted features.This algorithm is tested on several commonly used face databases.It is indicated that the performance is better than the traditional methods and common deep learning methods.
关键词:face recognition;improved deep networks;convolution;pooling;stacked sparse autoencoder
摘要:Presents a mode division multiplexing (MDM) system based on few-mode fiber bragg grating(FBG),the principle of the mode multiplexing/demultiplexing based on few-mode FBG is described.A 2×2 MDM system is established.The 10 km transmission experiment of the 1.25Gbps and 622Mbps PRBS is achieved successfully,which are carried by LP01 mode and LP11 mode,respectively.The eyediagrams after the 10 km two-mode fiber transmission are given.The BERs for LP01 and LP11 mode channel are analyzed when the laser operaes at 1549.228nm.The experimental results prove the feasibility of the mode division multiplexing system based on few-mode FBG,which provides the foundation for the further experiment of mode division multiplexing communication for long distance and high speed rate.
摘要:Curling-match design is a multi-constraint optimization problem which is hard to be converged.Therefore,a hierarchic optimization partheno-genetic algorithm is proposed.First,multiple constraint of the problem is layered;then,the targeted self-crossover operator is designed in the first layer optimization to ensure the convergence of the algorithm,while the fixed-random self-crossover operator is designed in the second layer optimization to maintain diversity of the population appropriately;finally,the proposed algorithm is used to solve the problem of curling-match design after building its fitness functions.Compared with the particle swarm algorithm and genetic algorithm,the simulation results demonstrate that the designed algorithm can solve the problem more efficiently.
摘要:The IEEE 1500 standard structure provides a test wrapper to test routers and a bypass to shield faulty routers.However,if a bypass fails,not only we cannot use it to tolerate fault,but also it will disturb other test responses in the same scan chain.To solve the problem,we propose a diagnostic method for bypass fault in routers' test wrapper in NoC.We use the Depth-first shortest path to get the shortest path from the scan-in port to the scan-out port,and we separate routers by using recursive partitioning stepwise refinement to construct multiple scan test chains.So the localization of bypass fault could be realized.Then we also propose an architecture to tolerate the bypass fault.
摘要:Brain tumor segmentation from medical images is a clinical requirement for brain tumor diagnosis and radiotherapy planning.However,automatic or semi-automatic segmentation of the brain tumor is still a challenging task due to the high diversities and the ambiguous boundaries in the appearance of tumor tissue.To solve this problem,we propose a brain tumor segmentation method based on softmax regression and graph model.Firstly,the training samples are labeled from the multi-modality magnetic resonance images(MRI).Then,the softmax regression method is used to train the samples to obtain the parameters of this regression model and calculate the probabilities of each pixel belonging to different labels.At last,the probabilities calculated in the previous step are introduced to a graph-cut based model.This model is minimized with a min-cut/max-flow method to obtain the final tumor segmentation results.The experiment results demonstrate superior performance in brain tumor segmentation.
摘要:According to the security problem caused by the malicious pilot contamination,this paper considers a three-node MIMO(Multple-Input Multiple-Output)network.First,the channel estimation results based on the least square criterion and the minimum mean square error criterion under the malicious pilot contamination are analyzed.Then by deducing the secrecy rate,we conclude that when the power of the pilot contamination from the eavesdropper is larger than that from the legitimate receiver,the secrecy rate is zero.Finally,the optimal power allocation schemes for the half-duplex and full-duplex eavesdropper are further studied,respectively.Simulation results show the effects of eavesdropping position,eavesdropping type,jamming power and other factors on the security performance.
关键词:physical layer security;malicious pilot contamination;secrecy rate;power allocation
摘要:A hardware Trojan detection method based on kernel maximum margin criterion and an improved detection method are proposed on basis of the statistical model of power side-channel signal.The methods can map the raw power side-channel signal into a higher dimensional space,where it had a higher separability,and then it is projected onto a low-dimensional subspace,so that non-linear characteristics of differences in the raw data are found,and nonlinear characteristics extraction and recognition of power side-channel signal are achieved.The detection experiment against the Trojan circuit in AES encryption circuit shows that,the number of samples beyond the detection boundary by the method (792) is more than Karhunen-Loève Transform (400),which gets a better detection result.
摘要:We propose a new code word selected scheme that directly selects code words to maximize the rate lower bound and combine bit allocation algorithm to reduce the sum rate loss,which is based on analyzing the disadvantages of the traditional limited feedback interference alignment scheme in two-cell interfering MIMO-MAC. Meanwhile,we adopt MAX-SINR criterion to decode the target signal. Unlike the traditional limited feedback schemes which are based on minimum chordal distance or alignment degree criterion,we select optimized code words from the perspective of maximizing the rate lower bound. Further,we generate the sets of code words which are close to perfect precoder,and select the optimized code words in these sets through low complexity and suboptimal global searching. The simulation results verify that the proposed algorithm effectively improves the performance of system and improves the rate lower bound compared with the existing typical algorithms.
关键词:interference alignment;MIMO-MAC;limited feedback;maximizing the rate lower bound;code words selected;bit allocation
摘要:X-ray image quality evaluation is the key problem of ray detection accuracy.The efficiency and real-time of the traditional subjective assessment method is poor.Also for some objective assessment indexes,such as contrast,definition,and so on,they have a certain limitation because of scatter and noise in the X-ray imaging.So this paper provides the method of X-ray image quality evaluation based on linear constraint with variable energy.First,based on the gray trend between the ray image sequences with variable energy imaging,the concept of the gray gain histogram between sequences is provided.Then based on the linear optimal imaging about imaging detector,evaluate image quality by the linear dispersion.Further,for the failure of dispersion evaluation because of over-exposure,synthesizing the linear dispersion and average contrast,the paper builds a standard of ray image quality evaluation.At last,the experiment proves the feasibility about this new standard.And it can avoid the limitation of the traditional single evaluation index.
关键词:X-ray imaging;image quality evaluation;varying energy imaging;linear dispersion;average contrast
摘要:To choose a better embedding position and strength of the digital watermark in Contourlet domain and overcome the defect that the last layer of the low frequency subband of the Contourlet transform are not divided,this paper put forward a construction method of the suppositional tree model.On this basis,combined with chaos technology,and utilizing fruit fly optimization Algorithm(FOA) to optimize the parameters of the support vector regression(SVR),a robust and adaptive watermarking scheme is proposed.The result shows that the algorithm owns better effect on robustness,security and invisibility.
关键词:digital watermark;contourlet transform;chaos technology;fruit fly optimization algorithm;suppositional tree model
摘要:Software defined networking(SDN) is a style of computer networking that separates the control plane from the data plane,shifting the control plane to a centralized controller in order to achieve network flexibility and openness.The controller placement is a key prerequisite to successful SDN.The current study examines the hierarchically distributed control plane controller placement problem,utilizing a multi-level k-way switch partition algorithm to divide large scale network topology.We also fix the traditional SDN controller placement problem,changing zoning and intra-domain controller placement by reducing the edge-cut in order to lower the number of inter-domain flows.Simulation results show that the multi-level k-way switch partition algorithm can effectively reduce control flow overhead and flow set-up time,compared with the other traditional algorithms.
关键词:software defined networking;controller placement;multi-level k-way switch partition
摘要:To automatically determine the number of clusters,a new fuzzy clustering algorithm is proposed in this study,which is based on soft partition scheme and integrates many FCM clustering results.In this method,FCM clustering is implemented on data by the cluster number;then the membership information is used to build a cumulative adjacency matrix;finally,the graph cut method is adopted to the cumulative adjacency matrix by iterative manner to obtain clustering results.Simulation experiments show that,compared to the current integrated clustering method,our method can effectively reduce the number of FCM clustering;furthermore,its iterations in the graph cut process is about 1/2 of the existing method.
摘要:Generally,traditional compressed sensing (CS) image recovery methods build the objective optimization function by using the signal sparsity in some specific feature spaces.They do not fully take the local features and structural properties of signal into account,which leads to constraints of the recovery performance and flexibility.In this paper,considering the non-local self-similarity (NLSS) in images,we propose an image CS reconstruction method based on the image low-rank property by converting the CS recovery problem into a matrix rank minimization problem of aggregating similar image patches.The proposed algorithm builds optimization model under the constraint of minimal recovery errors and employs the weighed nuclear norm minimization (WNNM) method to solve the low-rank optimization problem.By taking advantage of them,the proposed method exploits the self-information and structured sparse characteristics of the image very well,and therefore provides a better protection of image structures and textures.Experiments on different test images under various sampling rates have shown the effectiveness of the proposed algorithm.Especially,for richly-textured images,our method outperforms the art-of-the-state algorithms significantly under low sampling rates.
摘要:This paper develops a novel deformable object tracking algorithm based on max-pooling graph matching,which can be applied in the scenes with large deformations and severe occlusions.The dynamic graph is built based on candidate parts extracted by over-segmentation method from searching area,namely feature representation of candidate parts and geometric structure between them.Based on max-pooling graph matching method,the matching relations between target parts and candidate parts are found to calculate the confidence map of target location.Considering both the support of holistic target and local parts,the optimal target location can be determined.Compared to state-of-the-art methods,experimental results on several deformable sequences demonstrate the effectiveness and robustness of the proposed method.
摘要:Definitions of the desired co-polarization and cross-polarization directions are given for a scanned beampattern according to a desired polarization direction.Furthermore,the co-polarization directivity is defined to more accurately represents the degree of the concentration of co-polarization field over the total radiated power.With this definition,the co-polarization directivity can be optimized.Its analytical expression can be derived when no more pattern constraints exist.In more general cases in which the constraints on the sidelobe level,nulling points and cross-polarization level exist,an efficient numerical algorithm based on convex optimization is proposed.Some numerical synthesis experiments are conducted,and the results show the effectiveness and robustness of the proposed synthesis techniques.
摘要:Image matting is a process which separates the foreground object from the background scene,and the key of matting is to compute the alpha matte.The existing sampling based matting methods are always in a discretized strategy,which could results in a great deal of discontinuities and noises in final alpha mattes.Post processing is thus introduced to enhance the smoothness and to further increase the accuracy of the final matte.However,the corresponding review articles are still lacking in the field of international research of post-processing in image matting.Moreover,the quantitative evaluation of alpha mattes still remains unsolved.This paper firstly classifies the post-processing step into two basic categories: affinity-combined and self-smoothing.Next,the advantages and disadvantages are both summarized and analyzed.Finally,the alpha mattes after post-processing are evaluated in quantitative manner comprehensively,which improves the problem of pure visual evaluation in traditional methods.
摘要:Owing to the constraints of time and space complexity,support vector machine (SVM) faced with the problem of ‘curse of dimensionality’ when computation happens in high-dimensional feature space.Therefore,an intrusion detection model of support vector machine based on autoencoder network (AN-SVM) is proposed.First,the multilayer unsupervised restricted boltzmann machine (RBM) in our model is employed in mapping the vector of raw dada from high-dimensional nonlinear space to low-dimensional space,and a mutual mapping autoencoder network of high-dimensional space and low-dimensional space is constructed.Then autoencoder network weights of fine-tuning algorithm based on back propagation network is employed to reconstruct the new optimal high-dimensional representation of data in low-dimensional space,and the corresponding optimal low-dimensional representation of raw data can be obtained.Furthermore,SVM classification algorithm is employed to detect intrusion from the optimal low-dimensional data.The experimental results demonstrate that AN-SVM model can effectively reduce the training time and testing time of classifier in the intrusion detection model and its classification performance outperforms those traditional methods.So,AN-SVM model is a feasible and efficient lightweight intrusion detection model.
摘要:The clustering-based SoC test scheduling algorithm combined with the asynchronous clock periods testing is proposed to further reduce the SoC(System-on-Chip) test application time (TAT) and test cost.The scheduling algorithm pre-processes the test data by exploiting the characteristics of the tests.After conducting experiments on the ITC'02 SoC benchmark,we find out that the proposed scheduling method based on clustering can reduce TAT by 20.39% and 5.53% on average,when comparing with a synchronous clock testing method and an asynchronous method based on the MILP model,respectively.Besides,when the power constraint is tight,there is only a difference of 0.9% between the scheduling result and the lower bound.
关键词:SoC test scheduling;asynchronous clock;MILP model;clustering
摘要:The intentional attacks on the nodes makes the complex network very fragile under information condition,so it is very important to explore accurately and then protect these core nodes in the network.Based on analyzing the characteristics of communication network under the special condition,and taking the definition method of "amount of information" in the information communication system for reference,this paper propose a new evaluation method that are suitable for the directed-weighted networks.Through the comparative analysis of this method and the existing methods in small-scale mixed weighted network,the validity and advantage of this method is verified.The mixed weighted network evolution model based on BBV(Barrat-Barthelemy-Vespignani)is established,and the simulation which to evaluate the node importance in the generated large-scale communication network is performed.The experiment analysis results show that the proposed method may evaluate the node importance more easily and effectively than that of the state of the evaluation method.
摘要:Aimed at the problems of annotation of ground truth and the application of zooming,a new basic metric for visual tracking evaluation is proposed.Firstly,a weighted-overlap frame is reconstructed based on the traditional overlap.Secondly,we put forward multiple region annotation to decrease the deviation and apply in zooming.Thirdly,a multi-label fusion method is presented to improve the confidence level of the labels.Last but not least,the presented methods are expanded to repeated visual tracking evaluation,where a weighted result chart is utilized to make the evaluation more explanatory.Experimental results show that our annotation rule are more accurate than VOT and OTB,and the proposed metric is more appropriate than other metric.
摘要:In optical double-layer satellite network,the stability of network is determined by the OIOLs (Optical Inter-Orbit Links) seamless handover directly.Asynchronous handover method often results in frequent topology reconfiguration.However,synchronously centralized handover leads to cutoff of connection between two layers,and thus network operation condition gets out of control.A two-step synchronous handover scheme of MEO (Medium Earth Orbit) satellite and LEO (Low Earth Orbit) satellite constellation is proposed.Connection between LEO satellites and MEO satellites is guaranteed and topology reconstructing frequency is decreased.When orbit period of MEO satellite is integer multiple of LEO satellite,space position relation between LEO and MEO satellites is investigated.The second-order aspheric perturbation model of LEO satellite and MEO satellite constellation is built up.The orbit period ratio between MEO and LEO satellite is calculated as 3.The double-layer satellite network is designed.The laser links between the two layers in the elaborately configured LEO/MEO constellation pattern are divided into two groups based on connection and handover sequence.1/4 relative periods of the MEO satellite is considered as the handover criterion.In each 1/4 relative period,one group of inter-layer laser links switches synchronously.Research results show topology reconstructing frequency is reduced to 1/7 of link handover frequency.The average network time delay is decreased by 30ms compared with synchronously centralized handover method.