ISSN 
2012 Vol. 41, No. 1
2012, 41(1): 2-7.
doi: 10.3969/j.issn.1001-0548.2012.01.001
Abstract:
The mobility patterns of passengers in a public transport network are explored based on Shijiazhuang bus passengers survey data. The results show that the inflows and outflows of different stations in the network are strongly heterogeneous and the traffic flow among stations follows a power law distribution. The results also show that the travel distance distribution of public transport passengers is peaked, which can be fitted by a negative binomial distribution. The potential mechanism leading to these statistical characteristics are explained by three random walk models, one of which can reproduce the scaling distribution of traffic flow and the peaked distribution of travel distance.
The mobility patterns of passengers in a public transport network are explored based on Shijiazhuang bus passengers survey data. The results show that the inflows and outflows of different stations in the network are strongly heterogeneous and the traffic flow among stations follows a power law distribution. The results also show that the travel distance distribution of public transport passengers is peaked, which can be fitted by a negative binomial distribution. The potential mechanism leading to these statistical characteristics are explained by three random walk models, one of which can reproduce the scaling distribution of traffic flow and the peaked distribution of travel distance.
2012, 41(1): 8-16.
doi: 10.3969/j.issn.1001-0548.2012.01.002
Abstract:
Nowadays, mesoscales in complex networks has been an important topic of research in the field of complex networks. The paper presents the Laplacian spectral features of complex networks and reports the finding of a strong correlation between the laplacian spectrum and the node-degree sequence of a network. Furthermore, the synchronization and generalized synchronization of complex networks under different topological structures at the mesoscale level of description are studied. It is found that synchronization first starts from the nodes with largest degrees. It is also explored that the Laplacian spectrum shows a close relation with community structure and time scales regarding the network synchronization process. For community networks, there exists a general path towards synchronization: partial synchronization-cluster synchronization-global complete synchronization. This dynamical process helps to find the community structure of a network. Finally, some advanced researches of mesoscales in complex networks is introduced.
Nowadays, mesoscales in complex networks has been an important topic of research in the field of complex networks. The paper presents the Laplacian spectral features of complex networks and reports the finding of a strong correlation between the laplacian spectrum and the node-degree sequence of a network. Furthermore, the synchronization and generalized synchronization of complex networks under different topological structures at the mesoscale level of description are studied. It is found that synchronization first starts from the nodes with largest degrees. It is also explored that the Laplacian spectrum shows a close relation with community structure and time scales regarding the network synchronization process. For community networks, there exists a general path towards synchronization: partial synchronization-cluster synchronization-global complete synchronization. This dynamical process helps to find the community structure of a network. Finally, some advanced researches of mesoscales in complex networks is introduced.
2012, 41(1): 17-20.
doi: 10.3969/j.issn.1001-0548.2012.01.003
Abstract:
A numerical analysis is presented to show that the uniform allocation of cognitive users can maximize the communication opportunity capacity of cognitive radio networks. The optimal number of cognitive users and the corresponding algorithm of channel allocation are presented in this paper. Theory derivation and numerical analysis show that the optimal number of cognitive users is determined by the number of primary users, Channels and the communication requirement probability of cognitive users. In a given communication requirement probability of primary users, there is an optimal communication requirement probability of cognitive users which maximizes the communication opportunity capacity of cognitive radio networks. The proposed algorithm provides a theory basis for the configuration of cognitive radio networks.
A numerical analysis is presented to show that the uniform allocation of cognitive users can maximize the communication opportunity capacity of cognitive radio networks. The optimal number of cognitive users and the corresponding algorithm of channel allocation are presented in this paper. Theory derivation and numerical analysis show that the optimal number of cognitive users is determined by the number of primary users, Channels and the communication requirement probability of cognitive users. In a given communication requirement probability of primary users, there is an optimal communication requirement probability of cognitive users which maximizes the communication opportunity capacity of cognitive radio networks. The proposed algorithm provides a theory basis for the configuration of cognitive radio networks.
2012, 41(1): 21-24.
doi: 10.3969/j.issn.1001-0548.2012.01.004
Abstract:
Fourier transform is usually used in the domain of frequency-wave number transformation in ground penetrating radar. But the interpolation algorithm needs all the data in the domain of frequency migration. So discrete cosine transform (DCT) is presented to replace Fourier transform to do migration. According to the character of the concentration of energy of DCT, the interpolition processing is applied only to the data related with main components on DCT in the domain of frequency. Test result shows that DCT can be a good substitute to Fourier transform and suggested optimization algorithm has less computation and no plural parasitic data.
Fourier transform is usually used in the domain of frequency-wave number transformation in ground penetrating radar. But the interpolation algorithm needs all the data in the domain of frequency migration. So discrete cosine transform (DCT) is presented to replace Fourier transform to do migration. According to the character of the concentration of energy of DCT, the interpolition processing is applied only to the data related with main components on DCT in the domain of frequency. Test result shows that DCT can be a good substitute to Fourier transform and suggested optimization algorithm has less computation and no plural parasitic data.
2012, 41(1): 25-30.
doi: 10.3969/j.issn.1001-0548.2012.01.005
Abstract:
Spaceborne multi-input multi-output SAR (MIMO-SAR) system combined with multidimensional waveform encoding can obtain wider unambiguous swath width and higher azimuth resolution than traditional spaceborne SAR system. However, the mount of data of waveform diversity extraction method based on traditional digital beam-forming (DBF) techniques is seriously high and the great receive antenna gain loss from topography occurs with the recent presented scan-on-receive (SCORE) technique. A new waveform diversity extraction approach taking advantages of the SCORE technique via sub-array antennas and posterior space time processing (STP) is proposed in this paper. This approach can reduce the high date rate of SAR systems and the receiveing antenna gain loss from topography in the SCORE technique. Furthermore, this approach remains some useful information of multi-channel in elevation for other applications and it is easy to be realized. Simulation results validate the presented approach is better than the waveform diversity extraction method based on the SCORE technique.
Spaceborne multi-input multi-output SAR (MIMO-SAR) system combined with multidimensional waveform encoding can obtain wider unambiguous swath width and higher azimuth resolution than traditional spaceborne SAR system. However, the mount of data of waveform diversity extraction method based on traditional digital beam-forming (DBF) techniques is seriously high and the great receive antenna gain loss from topography occurs with the recent presented scan-on-receive (SCORE) technique. A new waveform diversity extraction approach taking advantages of the SCORE technique via sub-array antennas and posterior space time processing (STP) is proposed in this paper. This approach can reduce the high date rate of SAR systems and the receiveing antenna gain loss from topography in the SCORE technique. Furthermore, this approach remains some useful information of multi-channel in elevation for other applications and it is easy to be realized. Simulation results validate the presented approach is better than the waveform diversity extraction method based on the SCORE technique.
2012, 41(1): 31-35.
doi: 10.3969/j.issn.1001-0548.2012.01.006
Abstract:
A reduced-dimension space-time adaptive processing (STAP) method for clutter suppression in airborne multiple-input multiple-output (MIMO) radar systems is developed. Firstly, the high-dimensional weight vector is decomposed into the Kronecker product of spatial and temporal weight vectors. Secondly, the quadratic cost function used in the optimum STAP is converted into two quadratic functions by using the information of the space-time correlation matrix. Finally, by iteratively optimizing two lower dimensional weight vectors in two quadratic functions, the proposed method can significantly decrease the computational load and training samples requirement. Experimental results using both simulated data and measured radar data demonstrate the effectiveness of the proposed method.
A reduced-dimension space-time adaptive processing (STAP) method for clutter suppression in airborne multiple-input multiple-output (MIMO) radar systems is developed. Firstly, the high-dimensional weight vector is decomposed into the Kronecker product of spatial and temporal weight vectors. Secondly, the quadratic cost function used in the optimum STAP is converted into two quadratic functions by using the information of the space-time correlation matrix. Finally, by iteratively optimizing two lower dimensional weight vectors in two quadratic functions, the proposed method can significantly decrease the computational load and training samples requirement. Experimental results using both simulated data and measured radar data demonstrate the effectiveness of the proposed method.
2012, 41(1): 36-39,146.
doi: 10.3969/j.issn.1001-0548.2012.01.007
Abstract:
For adopting single time-frequency chuck as pilot pattern. We prove that the optimal estimation cannot be achieved by polynomial interpolation using the standard inverse matrix, when there are less pilot symbols than the parameters of the polynomial model. For solving this proldem, a generalized inverse matrix is defined from a weighting matrix which is constructed based on minimum variance criterion. A 2-D polynomial interpolation algorithm is then proposed based on this weighted generalized inverse matrix. Simulation result shows that the proposed algorithm can be applied to receivers with different velocities. Under moderate or low velocity in particular, this algorithm can achieve a BER gain of about 2 dB for large SNR compared with 1-D linear Interpolation algorithms.
For adopting single time-frequency chuck as pilot pattern. We prove that the optimal estimation cannot be achieved by polynomial interpolation using the standard inverse matrix, when there are less pilot symbols than the parameters of the polynomial model. For solving this proldem, a generalized inverse matrix is defined from a weighting matrix which is constructed based on minimum variance criterion. A 2-D polynomial interpolation algorithm is then proposed based on this weighted generalized inverse matrix. Simulation result shows that the proposed algorithm can be applied to receivers with different velocities. Under moderate or low velocity in particular, this algorithm can achieve a BER gain of about 2 dB for large SNR compared with 1-D linear Interpolation algorithms.
2012, 41(1): 40-42.
doi: 10.3969/j.issn.1001-0548.2012.01.008
Abstract:
The electro-optic effect of a silica microfiber knot resonator (MKR) is studied. The characteristic of output optical spectrum is analyzed theoretically and experimentally. The experimental results show that the current sensitivity due to electro-optic effect is~500 pm/A. The wavelength shift due to the thermal drift of the wire is much smaller than that caused by the electro-optic effect. Such MKR has the advantages of high Q factor, compact size and low cost and therefore has potential value in developing tunable in-line fiber-optic filters and micro-current measurement for MEMS devices.
The electro-optic effect of a silica microfiber knot resonator (MKR) is studied. The characteristic of output optical spectrum is analyzed theoretically and experimentally. The experimental results show that the current sensitivity due to electro-optic effect is~500 pm/A. The wavelength shift due to the thermal drift of the wire is much smaller than that caused by the electro-optic effect. Such MKR has the advantages of high Q factor, compact size and low cost and therefore has potential value in developing tunable in-line fiber-optic filters and micro-current measurement for MEMS devices.
2012, 41(1): 43-47.
doi: 10.3969/j.issn.1001-0548.2012.01.009
Abstract:
Aiming to obtain a low sidelobe of an array, fuzzy discrete particle swarm optimization (FDPSO) algorithm is firstly applied in the optimization of the element positions of thinned antenna arrays. Compared with some evolutionary algorithms such as genetic algorithm, the FDPSO has the advantages of less parameters and easier to be implemented. In order to avoid the algorithm being trapped into local optimum, a chaotic dynamic procedure is introduced in the optimization. A penalty approach is used in the constraint of the width of mainlobe. Simulation results of a linear array show that the algorithm can handle discrete problem properly.
Aiming to obtain a low sidelobe of an array, fuzzy discrete particle swarm optimization (FDPSO) algorithm is firstly applied in the optimization of the element positions of thinned antenna arrays. Compared with some evolutionary algorithms such as genetic algorithm, the FDPSO has the advantages of less parameters and easier to be implemented. In order to avoid the algorithm being trapped into local optimum, a chaotic dynamic procedure is introduced in the optimization. A penalty approach is used in the constraint of the width of mainlobe. Simulation results of a linear array show that the algorithm can handle discrete problem properly.
2012, 41(1): 48-53.
doi: 10.3969/j.issn.1001-0548.2011.04.010
Abstract:
In this paper, the computer implementation of optimal index-order of binary decision diagram (BDD) structure is researched based on analyzing the principle of optimal index-order presented by Friedman etc. In process of analyzing key techniques, the redundancy to store truth table of all indexes in original method is pointed out. At the same time, the defect that the original method could only obtain an optimal solution (when the object had several optimal solutions) was analyzed, and then the original method was improved, i.e., the truth table used for storing index value is deleted and the algorithm is modified to get all optimal solutions. To realize optimal BDD structure in formality, the principle simplifying ‘equivalent' nodes with ‘deleting' operations is analyzed in detail. The theory of optimal index-order and method of simplifying ‘equivalent' nodes are united to implement optimal BDD structure with theoretic and formal angle. Finally, the advantages of joint improved method used for achieving optimal BDD structure are validated with an example.
In this paper, the computer implementation of optimal index-order of binary decision diagram (BDD) structure is researched based on analyzing the principle of optimal index-order presented by Friedman etc. In process of analyzing key techniques, the redundancy to store truth table of all indexes in original method is pointed out. At the same time, the defect that the original method could only obtain an optimal solution (when the object had several optimal solutions) was analyzed, and then the original method was improved, i.e., the truth table used for storing index value is deleted and the algorithm is modified to get all optimal solutions. To realize optimal BDD structure in formality, the principle simplifying ‘equivalent' nodes with ‘deleting' operations is analyzed in detail. The theory of optimal index-order and method of simplifying ‘equivalent' nodes are united to implement optimal BDD structure with theoretic and formal angle. Finally, the advantages of joint improved method used for achieving optimal BDD structure are validated with an example.
2012, 41(1): 54-59.
doi: 10.3969/j.issn.1001-0548.2012.01.011
Abstract:
For a class of uncertain affine nonlinear systems with unknown boundary functions, an adaptive fuzzy controller (AFC) with the characteristic of high tracking accuracy is proposed in this paper. Based on the theory of variable universe fuzzy system, it is proved that the optimal fuzzy approximation error (FAE) has local convergence property under certain conditions. By using the tracking errors as inputs and selecting suitable adaptive parameters, an AFC with optimal FAE local convergence is developed. Under the key assumption that the optimal FAE is bounded, it is proved that the closed-loop system is stable in the sense that all involving variables are bounded and the tracking errors converge to zero. This approach can theoretically eliminate the effect of the FAE on the tracking errors without additional compensator, thus it can achieve high tracking accuracy with smooth control input. Simulated application of a single-link manipulator demonstrates the effectiveness of this approach.
For a class of uncertain affine nonlinear systems with unknown boundary functions, an adaptive fuzzy controller (AFC) with the characteristic of high tracking accuracy is proposed in this paper. Based on the theory of variable universe fuzzy system, it is proved that the optimal fuzzy approximation error (FAE) has local convergence property under certain conditions. By using the tracking errors as inputs and selecting suitable adaptive parameters, an AFC with optimal FAE local convergence is developed. Under the key assumption that the optimal FAE is bounded, it is proved that the closed-loop system is stable in the sense that all involving variables are bounded and the tracking errors converge to zero. This approach can theoretically eliminate the effect of the FAE on the tracking errors without additional compensator, thus it can achieve high tracking accuracy with smooth control input. Simulated application of a single-link manipulator demonstrates the effectiveness of this approach.
2012, 41(1): 60-64.
doi: 10.3969/j.issn.1001-0548.2012.01.012
Abstract:
Considering the difficulty inherent in the measurement of via holes with vector network analyzer the measurement of via hole structures. The design of device under test, test fixture, test connection, boundary conditions, calibrations, and the de-embedding method are presented and experimented actually, the operating frequency covers from 10 MHz to 20 GHz. Comparison with former result, the advert side-effects caused by test connection and fixture has been removed, and furthermore, the more accurate characteristic of via holes can be acquired.
Considering the difficulty inherent in the measurement of via holes with vector network analyzer the measurement of via hole structures. The design of device under test, test fixture, test connection, boundary conditions, calibrations, and the de-embedding method are presented and experimented actually, the operating frequency covers from 10 MHz to 20 GHz. Comparison with former result, the advert side-effects caused by test connection and fixture has been removed, and furthermore, the more accurate characteristic of via holes can be acquired.
2012, 41(1): 65-69.
doi: 10.3969/j.issn.1001-0548.2012.01.013
Abstract:
Biogeography-based optimization (BBO) is a new intelligent optimization algorithm, which has better search efficiency than the previous intelligent optimization algorithms, but it also has premature convergence. To solve this problem, biogeography-based optimization algorithm by suing chaotic search (CSBBO) is proposed. Firstly initial populations are generated based on piecewise chaotic map, then BBO global search algorithm is used to get the current optimal solution, finally the global optimum is obtained by using chaotic search. Simulation results show that CSBBO outperforms BBO and previous intelligent optimization algorithms in terms of convergence rate and search precision.
Biogeography-based optimization (BBO) is a new intelligent optimization algorithm, which has better search efficiency than the previous intelligent optimization algorithms, but it also has premature convergence. To solve this problem, biogeography-based optimization algorithm by suing chaotic search (CSBBO) is proposed. Firstly initial populations are generated based on piecewise chaotic map, then BBO global search algorithm is used to get the current optimal solution, finally the global optimum is obtained by using chaotic search. Simulation results show that CSBBO outperforms BBO and previous intelligent optimization algorithms in terms of convergence rate and search precision.
2012, 41(1): 70-73.
doi: 10.3969/j.issn.1001-0548.2012.01.014
Abstract:
User access patterns reflect the laws of the user browsing the sites and the interest of user's access. The common pattern discovery method is mining frequent traversal paths of the user from the user's access logs. As the mining method of the frequent traversal path based on Apriori algorithm needs frequent access to the database and produce large amounts of candidate items, this paper presents a new data structure of the traverse path tree to mine user's frequent traversal paths. Results show that the mining efficiency is improved comparing with the traditional method.
User access patterns reflect the laws of the user browsing the sites and the interest of user's access. The common pattern discovery method is mining frequent traversal paths of the user from the user's access logs. As the mining method of the frequent traversal path based on Apriori algorithm needs frequent access to the database and produce large amounts of candidate items, this paper presents a new data structure of the traverse path tree to mine user's frequent traversal paths. Results show that the mining efficiency is improved comparing with the traditional method.
2012, 41(1): 74-79.
doi: 10.3969/j.issn.1001-0548.2012.01.015
Abstract:
To assure the trustworthiness of high-trusted architecture of embedded operating system that named Hades, the inter-partition information flow of Hades must be controlled strictly. By analyzing the limitation of existing methods, we present a new information flow control model and construct a information flow mechanism between partitions. The accuracy of these model and mechanism are verified through the experiment.
To assure the trustworthiness of high-trusted architecture of embedded operating system that named Hades, the inter-partition information flow of Hades must be controlled strictly. By analyzing the limitation of existing methods, we present a new information flow control model and construct a information flow mechanism between partitions. The accuracy of these model and mechanism are verified through the experiment.
2012, 41(1): 80-84.
doi: 10.3969/j.issn.1001-0548.2012.01.016
Abstract:
A novel calibration optimization method for delay-control systems is proposed. A multi-objective optimization function, considering both precision and reliability, is introduced to handle the calibration problem. Genetic algorithm (GA) is used to solve the optimization function, in which adaptive crossover and mutation algorithm are applied to improve the convergence performance of GA. Good performance of precision and reliability is demonstrated by numerical results.
A novel calibration optimization method for delay-control systems is proposed. A multi-objective optimization function, considering both precision and reliability, is introduced to handle the calibration problem. Genetic algorithm (GA) is used to solve the optimization function, in which adaptive crossover and mutation algorithm are applied to improve the convergence performance of GA. Good performance of precision and reliability is demonstrated by numerical results.
2012, 41(1): 85-91.
doi: 10.3969/j.issn.1001-0548.2012.01.017
Abstract:
Memory latency has become a critical bottleneck in achieving high performance on modern processors. Prefetching thread based on multiprocessor (CMP) is a well known approach to reducing memory latency and has been explored in different applications. In this paper, we analyze the performance of prefetching thread for memory intensive applications. The analysis and experimental result show that computation/access latency ratio (CALR) of hotspots has an important affect on prefethcing performance. When the memory access ratio between main thread and prefetching thread is close to (1-CALR)/(1+CALR), prefetching thread gains better performance. The thread prefetching performance of several benchmarks from Olden and SPEC2006 benchmark suite is tested, and the experimental results reflect the impact of different memory access ratio between Prefetching thread and main thread.
Memory latency has become a critical bottleneck in achieving high performance on modern processors. Prefetching thread based on multiprocessor (CMP) is a well known approach to reducing memory latency and has been explored in different applications. In this paper, we analyze the performance of prefetching thread for memory intensive applications. The analysis and experimental result show that computation/access latency ratio (CALR) of hotspots has an important affect on prefethcing performance. When the memory access ratio between main thread and prefetching thread is close to (1-CALR)/(1+CALR), prefetching thread gains better performance. The thread prefetching performance of several benchmarks from Olden and SPEC2006 benchmark suite is tested, and the experimental results reflect the impact of different memory access ratio between Prefetching thread and main thread.
2012, 41(1): 92-97.
doi: 10.3969/j.issn.1001-0548.2012.01.018
Abstract:
With the widely use of acceleration devices, hardware parallelism of single hybrid programming computer (HPC) node has increased many. As a result, both on-chip communication and inter-node communication become more and more frequently. Apparently, communication is becoming the bottleneck of system performance. This paper proposes a design of hardware module called synchronization accelerator to accelerate synchronization communication patterns. These patterns include fine-grain synchronization, barrier, and all-reduce. At the scale of 16 processes, synchronization accelerator can achieve about 4 times speedup than software-based collective operations. Also, the performance of benchmark LU can achieve 20% improvement with the use of synchronization accelerator.
With the widely use of acceleration devices, hardware parallelism of single hybrid programming computer (HPC) node has increased many. As a result, both on-chip communication and inter-node communication become more and more frequently. Apparently, communication is becoming the bottleneck of system performance. This paper proposes a design of hardware module called synchronization accelerator to accelerate synchronization communication patterns. These patterns include fine-grain synchronization, barrier, and all-reduce. At the scale of 16 processes, synchronization accelerator can achieve about 4 times speedup than software-based collective operations. Also, the performance of benchmark LU can achieve 20% improvement with the use of synchronization accelerator.
2012, 41(1): 98-103.
doi: 10.3969/j.issn.1001-0548.2012.01.019
Abstract:
The mathematical model of virus propagation in the mobile peer-to-peer(MP2P) networks is proposed by applying Epidemiology. Based on the proposed model and using the special digital-analysis software Matlab, large-scale experiments are done so as to examine the effect of the MP2P-related parameters on virus propagation. The results of these experiments illustrate that different parameters have different effects on virus propagation, among which the average downloading rate and the average recovery rate of fixed peers have the strongest effects on virus propagation.
The mathematical model of virus propagation in the mobile peer-to-peer(MP2P) networks is proposed by applying Epidemiology. Based on the proposed model and using the special digital-analysis software Matlab, large-scale experiments are done so as to examine the effect of the MP2P-related parameters on virus propagation. The results of these experiments illustrate that different parameters have different effects on virus propagation, among which the average downloading rate and the average recovery rate of fixed peers have the strongest effects on virus propagation.
2012, 41(1): 104-109.
doi: 10.3969/j.issn.1001-0548.2012.01.020
Abstract:
A new associative classification method named ACCF is presented based on the closed frequent itemsets. This method first mines all closed frequent itemsets and the candidate class association rules (CARs), and then constructs classifier based the selected CARs from the candidate CARS. The new instances are finally classified by a new way. Our theoretical analysis and substantial experiments on 18 datasets from UCI repository of machine learning databases show that ACCF is highly effective at classification of various kinds of datasets. Compared with the typical associative classification algorithms, ACCF can mine much less CARs and has higher average classification accuracy.
A new associative classification method named ACCF is presented based on the closed frequent itemsets. This method first mines all closed frequent itemsets and the candidate class association rules (CARs), and then constructs classifier based the selected CARs from the candidate CARS. The new instances are finally classified by a new way. Our theoretical analysis and substantial experiments on 18 datasets from UCI repository of machine learning databases show that ACCF is highly effective at classification of various kinds of datasets. Compared with the typical associative classification algorithms, ACCF can mine much less CARs and has higher average classification accuracy.
2012, 41(1): 110-113.
doi: 10.3969/j.issn.1001-0548.2012.01.021
Abstract:
This paper proposes a grey scale image matching algorithm with NVIDIA CUDA in order to accelerate the process using GPU. Our test shows that when matching on the same image, the CUDA program of grey-level image matching algorithm is 40 times faster than the CPU with MPI version, without the decline of matching precision. The result shows that the grey scale image mathing can be applied to real-time applications such as interactive systems.
This paper proposes a grey scale image matching algorithm with NVIDIA CUDA in order to accelerate the process using GPU. Our test shows that when matching on the same image, the CUDA program of grey-level image matching algorithm is 40 times faster than the CPU with MPI version, without the decline of matching precision. The result shows that the grey scale image mathing can be applied to real-time applications such as interactive systems.
2012, 41(1): 114-119.
doi: 10.3969/j.issn.1001-0548.2012.01.022
Abstract:
Through analyzing existing methods of median filtering on salt & pepper noise, a new improved weighted median filtering based on grads similarity is proposed. The proposed algorithm divides the image with salt & pepper noise into uncertain noise pixel and signal pixel from the difference of pixel grey value in filtering window. The uncertain noise pixels are further analyzed by grads similarity in filtering window. The disturbance of noise pixel is removed by applying extremum trimming method. At last, a improved weighted median filtering algorithm with abandon points of max square deviation is used to compute the grey value of noisy point. Simulation results show that this proposed method has a great improvement in removing salt & pepper noise and preserving the details of image. The restored image can also obtain better peak signal to noise ratio (PSNR).
Through analyzing existing methods of median filtering on salt & pepper noise, a new improved weighted median filtering based on grads similarity is proposed. The proposed algorithm divides the image with salt & pepper noise into uncertain noise pixel and signal pixel from the difference of pixel grey value in filtering window. The uncertain noise pixels are further analyzed by grads similarity in filtering window. The disturbance of noise pixel is removed by applying extremum trimming method. At last, a improved weighted median filtering algorithm with abandon points of max square deviation is used to compute the grey value of noisy point. Simulation results show that this proposed method has a great improvement in removing salt & pepper noise and preserving the details of image. The restored image can also obtain better peak signal to noise ratio (PSNR).
2012, 41(1): 120-124.
doi: 10.3969/j.issn.1001-0548.2012.01.023
Abstract:
A new smooth space image restoration model based on DT model, Jiang model, and LHLLAV model is considered. The meanings of the parameters of the new model is discussed. The definition, nature, and norm of Besov space and Gp,qβ space are described. The model in Gp,qβ space is re-described according to the relationship between Gp,qβ space and Besov space. By constructing a surrogate functional that removes the influence of K*Ku, the model solution in the second generation curvelet transform domain is derived and an elegant curvelet shrinkage schemes is obtained. The experiment study shows that the new method has better restoration effect, faster convergence, and lower computational complexity than LHLLAV model.
A new smooth space image restoration model based on DT model, Jiang model, and LHLLAV model is considered. The meanings of the parameters of the new model is discussed. The definition, nature, and norm of Besov space and Gp,qβ space are described. The model in Gp,qβ space is re-described according to the relationship between Gp,qβ space and Besov space. By constructing a surrogate functional that removes the influence of K*Ku, the model solution in the second generation curvelet transform domain is derived and an elegant curvelet shrinkage schemes is obtained. The experiment study shows that the new method has better restoration effect, faster convergence, and lower computational complexity than LHLLAV model.
2012, 41(1): 125-130.
doi: 10.3969/j.issn.1001-0548.2012.01.024
Abstract:
A suicide based defensive approach is proposed in this paper. In this novel defensive solution, a set of defensive nodes with capacity of detecting P2P worms will be deployed into a P2P network. While P2P worms break out, these defensive nodes will collect P2P worm data to construct a detection model to prevent the spreading of P2P worms. First, these defensive nodes will suicide to avoid being infected and exploited after P2P worm breaking out. Furthermore, each suicide node will also send a warning message to its neighbors to take preventive actions.
A suicide based defensive approach is proposed in this paper. In this novel defensive solution, a set of defensive nodes with capacity of detecting P2P worms will be deployed into a P2P network. While P2P worms break out, these defensive nodes will collect P2P worm data to construct a detection model to prevent the spreading of P2P worms. First, these defensive nodes will suicide to avoid being infected and exploited after P2P worm breaking out. Furthermore, each suicide node will also send a warning message to its neighbors to take preventive actions.
2012, 41(1): 131-135.
doi: 10.3969/j.issn.1001-0548.2012.01.025
Abstract:
Starting from the extended event process chain (EEPC) and traditional Petri net, the extended Petri net model based on EEPC is proposed. This model can reflect the logical structure of the process, make a quantitative calculation and judgment of such factors as time, thus guaranteeing the correctness and validity of the process analysis qualitatively and quantitatively. Each step of this new model is introduced. The proposed model is validated through a real-world hospital BPR case study.
Starting from the extended event process chain (EEPC) and traditional Petri net, the extended Petri net model based on EEPC is proposed. This model can reflect the logical structure of the process, make a quantitative calculation and judgment of such factors as time, thus guaranteeing the correctness and validity of the process analysis qualitatively and quantitatively. Each step of this new model is introduced. The proposed model is validated through a real-world hospital BPR case study.
2012, 41(1): 136-141.
doi: 10.3969/j.issn.1001-0548.2012.01.026
Abstract:
The low-power design of multi-core DSP has become more and more important. According to the baseband digital signal processing features, this paper proposes a data-driven and task-driven gated clock method to control the DSP core's on and off in the multi-core DSP. Experimental results show that multi-core DSP design using the proposed method has good power performance.
The low-power design of multi-core DSP has become more and more important. According to the baseband digital signal processing features, this paper proposes a data-driven and task-driven gated clock method to control the DSP core's on and off in the multi-core DSP. Experimental results show that multi-core DSP design using the proposed method has good power performance.
2012, 41(1): 142-146.
doi: 10.3969/j.issn.1001-0548.2012.01.027
Abstract:
On the demand of Consultative Committee for Space Date Systems (CCSDS) standardization for international cooperation in space exploration, the method of blind recognition of telecommand (TC) transfer frame is researched. After a discussion of the characteristics of CCSDS link protocol, a blind synchronization method based on pattern matching is proposed for communications link transmission unit (CLTU) and the performance of algorithm is analyzed. An implementation of BCH (63, 56) decoder is given and some fields of TC frames are extracted. The general concept presented here is applicable to recognition of CCSDS data link protocol and is a good reference to protocol identification in space information countermeasures.
On the demand of Consultative Committee for Space Date Systems (CCSDS) standardization for international cooperation in space exploration, the method of blind recognition of telecommand (TC) transfer frame is researched. After a discussion of the characteristics of CCSDS link protocol, a blind synchronization method based on pattern matching is proposed for communications link transmission unit (CLTU) and the performance of algorithm is analyzed. An implementation of BCH (63, 56) decoder is given and some fields of TC frames are extracted. The general concept presented here is applicable to recognition of CCSDS data link protocol and is a good reference to protocol identification in space information countermeasures.
2012, 41(1): 147-151.
doi: 10.3969/j.issn.1001-0548.2012.01.028
Abstract:
This paper proposes a new coordinates system (T-Vivaldi) which uses a mechanism to detect and restrict triangle inequality violations. The mechanism can detect TIV with triangle inequality qualification, use a parameter to quantify its degree, and restrict TIV through restricting coordinates update with the parameter. The simulation results show that: compared with Vivaldi, T-Vivaldi can restrict the impact of TIV and increase the predicting accuracy.
This paper proposes a new coordinates system (T-Vivaldi) which uses a mechanism to detect and restrict triangle inequality violations. The mechanism can detect TIV with triangle inequality qualification, use a parameter to quantify its degree, and restrict TIV through restricting coordinates update with the parameter. The simulation results show that: compared with Vivaldi, T-Vivaldi can restrict the impact of TIV and increase the predicting accuracy.
2012, 41(1): 152-157.
doi: 10.3969/j.issn.1001-0548.2012.01.029
Abstract:
Traffic matrix estimation problem remains one of the research focus for network designer and administrator for many years, especially the traffic estimation of back-bone networks for ISPs. In this article, we introduce betweenness centrality as the measure index of candidate snapshots and group betweenness centrality (GBC) particularly for choosing multiple link weight changes. Our experiments show that the introduction of BC actually accelerates the increase of ranks, and GBC reflects the influences of different group sizes. Some considerations are suggested for further research.
Traffic matrix estimation problem remains one of the research focus for network designer and administrator for many years, especially the traffic estimation of back-bone networks for ISPs. In this article, we introduce betweenness centrality as the measure index of candidate snapshots and group betweenness centrality (GBC) particularly for choosing multiple link weight changes. Our experiments show that the introduction of BC actually accelerates the increase of ranks, and GBC reflects the influences of different group sizes. Some considerations are suggested for further research.
2012, 41(1): 158-160.
doi: 10.3969/j.issn.1001-0548.2012.01.030
Abstract:
In order to realize real-time voice processing, a parallel access design based on FPGA is proposed. Low memory space is implemented by distributed CLBs while the high memory space is constructed by the embedded arrays on FPGA. The mapping from logical memory to physical memory is introduced. With the help of dynamical replacement algorithm, the frequently accessed memory block is mapped into low memory space. Our experiment results show that, the dynamic replacement algorithm keeps memory access performance in a suitable range.
In order to realize real-time voice processing, a parallel access design based on FPGA is proposed. Low memory space is implemented by distributed CLBs while the high memory space is constructed by the embedded arrays on FPGA. The mapping from logical memory to physical memory is introduced. With the help of dynamical replacement algorithm, the frequently accessed memory block is mapped into low memory space. Our experiment results show that, the dynamic replacement algorithm keeps memory access performance in a suitable range.
