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    25 December 2018, Volume 39 Issue 12
    Papers
    Unified study on characteristic spectrum representation of signals and spectral decomposition for stationary random signals
    Hongyu WANG,Tianshuang QIU
    2018, 39(12):  1-9.  doi:10.11959/j.issn.1000-436x.2018219
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    The unified relationship between the signal characteristic spectrum representation and the spectral decomposition for the stationary random signal was deeply studied. By using the relations among the differential operators, the integral operator and the Green's function of the characteristic differential equation, the inverse relationship between the Hermitian differential operator and the Hermitian integral operator were given, the characteristic differential equation and corresponding characteristic integral equation were demonstrated, and the spectral representations of both Hermitian differential and integral operators and the general spectral representations for both operators were provided. Based on the superposition method of the stochastic simple harmonic vibration and the Hilbert space unitary operator method for the stationary random signal spectral decomposition, the connection and unification on mathematics of the signal characteristic spectral representation and the stationary random signal spectral decomposition are revealed.

    Metric and classification model for privacy data based on Shannon information entropy and BP neural network
    Yihan YU,Yu FU,Xiaoping WU
    2018, 39(12):  10-17.  doi:10.11959/j.issn.1000-436x.2018286
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    Aiming at the requirements of privacy metric and classification for the difficulty of private data identification in current network environment, a privacy data metric and classification model based on Shannon information entropy and BP neural network was proposed. The model establishes two layers of privacy metrics from three dimensions. Based on the dataset itself, Shannon information entropy was used to weight the secondary privacy elements, and the privacy of each record in the dataset under the first-level privacy metrics was calculated. The trained BP neural network was used to output the classification result of privacy data without pre-determining the metric weight. Experiments show that the model can measure and classify private data with low false rate and small misjudged deviation.

    Improved artificial bee colony algorithm for large scale colored bottleneck traveling salesman problem
    Wenyong DONG,Xueshi DONG,Yufeng WANG
    2018, 39(12):  18-29.  doi:10.11959/j.issn.1000-436x.2018284
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    In the fields such as intelligent transport and multiple tasks cooperation, the model scale constructed by colored bottleneck traveling salesman problem (CBTSP) tends to large scale, and therefore it is necessary to study the large scale CBTSP and its algorithms. An improved artificial bee colony algorithm (IABC) was applied to solve the large scale CBTSP. IABC employed generating neighboring solution (GNS) to improve artificial bee colony algorithm for CBTSP. GNS generated new solution by deletion and reinsertion operations, during this process, and it can optimized the existed solution for this problem. Experiments show that IABC can demonstrate better solution quality than other compared algorithms for large scale CBTSP.

    Correlation coefficient measurement for conflict evidence
    Guidong SUN,Xin GUAN,Xiao YI,Jing ZHAO
    2018, 39(12):  30-39.  doi:10.11959/j.issn.1000-436x.2018277
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    The complex battlefield environment increases the uncertainty of reconnaissance information processing, so the uncertain information processing is investigated, especially the conflict evidence measurement, based on the belief functions. The normalized evidence correlation is defined as the correlation coefficient measurement for conflict evidence. In order to solve the drawback that the existing conflict evidence measurement methods do not distinguish the single set and multiple sets, the union core and core relational matrix are defined to modify the union core and core correlation respectively and further obtain the modified conflict evidence measurement. Finally, the efficiency of the proposed correlation coefficient measurement for conflict evidence is illustrated in the classical simulation example.

    Feature extraction algorithm based on quaternion common spatial pattern for banknote recognition
    Shan GAI
    2018, 39(12):  40-46.  doi:10.11959/j.issn.1000-436x.2018285
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    New feature extraction algorithm was proposed based on quaternion common spatial pattern in order to solve the lack of effective description of phase information in the banknote feature extraction and analysis. Firstly, the quaternion matrix was utilized to describe the phase information of the banknote image, and made diagonalization of quaternion composite Hermitian matrix. Secondly, the sample vector was input to the composite quaternion filter. The extracted feature vector was obtained by using the variance of the real part and imaginary part. Finally, the neural network was applied as classifier and the reject class was introduced in the banknote recognition. The experimental results illustrate that the proposed algorithm obtains high recognition rate and meets the real-time requirement of the banknote recognition system. The proposed algorithm has already been applied in a resource-constrained embedded system at the same time.

    VehLoc: an in-vehicle high-precision location method based on BLE multi-channel RSSI values
    Ze ZHAO,Yuan GAO,Li CUI
    2018, 39(12):  47-59.  doi:10.11959/j.issn.1000-436x.2018280
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    High precision in-vehicle positioning is the basis of providing smart in-vehicle service, passengers' behavior analysis and other issues, and has important practical value. The RSSI (received signal strength indicator) values of BLE (bluetooth low energy) can be used to do analysis and computation in location system. To deal with the problem that RSSI is vulnerable to environmental issues, an in-vehicle location method called VehLoc based on BLE multi-channel multi-RSSI values was proposed. By using a plurality of Bluetooth transmitters, the location of the receiving terminals in the vehicle was analyzed by combining the coarse, fine classifier and distribution fitting of the user's RSSI values in different channels. The experimental results show that the average accuracy of VehLoc in the five main positions in-vehicle classification can reach 90%.

    Feature selection algorithm based on improved particle swarm joint taboo search
    Zhen ZHANG,Peng WEI,Yufeng LI,Julong LAN,Ping XU,Bo CHEN
    2018, 39(12):  60-68.  doi:10.11959/j.issn.1000?436x.2018287
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    To solve the problem of high data feature dimensionality in intrusion detection, a feature selection algorithm based on improved particle swarm optimization taboo search (IPSO-TS) was proposed. The genetic algorithm was used to improve the particle swarm optimization, and the initial optimal solution of feature selection was obtained. A taboo search (TS) algorithm was used for initial optimal solution to obtain the global optimal solution of the feature subset. Compared with genetic algorithm integrated particle swarm optimization (CMPSO), particle swarm optimization (PSO) and PSO-TS algorithms, experimental results based on the KDD CUP 99 dataset show that the method reduces the features by about 29.2% , shortens about 15% of the average detection time, and increases about 2.96% of the average classification accuracy.

    High sensitivity optical detection method based on photon RF oscillator
    Ning MU,Wanrong GAO,Wanghan LYU
    2018, 39(12):  69-74.  doi:10.11959/j.issn.1000-436x.2018288
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    Based on the research of optical coherent detection in complex background, a new type of laser superheterodyne detection method was proposed, which based on a photon radio frequency technology. Firstly a system by photon RF oscillation mechanism and mathematical model was constructed. The principle of constructing the system was deduced and analyzed. The correctness of the method was verified by theoretical simulation and experiment. Compared with the traditional technology, the proposed method can improve the sensitivity of optical detection by several orders of magnitude, and can effectively suppress the influence of background dispersion spectrum on target information detection.

    Pilot scheduling algorithm based on cell classification-cross entropy for massive MIMO
    Yinhui YU,Heng ZHOU,Ying YANG,Hao PAN,Jiapeng REN
    2018, 39(12):  75-81.  doi:10.11959/j.issn.1000-436x.2018289
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    The massive MIMO system is equipped with a large number of antennas at the base station to serve many users, but it is affected by the inter-cell interference which called pilot contamination. A pilot scheduling scheme was designed to reduce the effect of pilot contamination. Pilot scheduling problem belongs to the arrangement optimization problem, and the algorithm computational complexity of greedy algorithm to search the optimal solution is greatly. In order to reduce the influence of the interference of the community, a new pilot scheduling schemes was proposed by so this article using cell classification and cross entropy(CE) mechanism to reduce the effect of pilot contamination on the system. The simulation results show that the proposed algorithm can not only improve the performance of the system, but also reduce the computational complexity.

    Analysis and verification of safety computer time constraints for train-to-train communications
    Ying GAO,Yuan CAO,Yongkui SUN,Lianchuan MA,Chunhua HONG,Yuzhuo ZHANG
    2018, 39(12):  82-90.  doi:10.11959/j.issn.1000?436x.2018275
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    In order to adapt to the development trend of the communication based train control (CBTC) system from train-ground communication mode to train-to-train communication mode, a verification approach for time constraints of multi-period applications concurrence on-board safety computer based on time Petri net was proposed. By taking the double 2 out of 2 on-board safety computer as an example, the multi-period applications concurrence nature of the safety computer was analyzed. Time Petri net (TPN) was utilized to calculate the time schedulable interval. Then several cases were analyzed based on the inference of this approach. The analysis and verification results indicate that onboard safety computer can meet the time constraints of more than three periodic safety-critical applications under the condition of single-core with main frequency of 1GHz, which demonstrates the effectiveness of verifying and evaluating the time constraints of safety computer periodic applications using TPN.

    Energy balanced routing algorithm for opportunistic network based on message importance
    Zhigang CHEN,NBin'an YI,Jia WU
    2018, 39(12):  91-101.  doi:10.11959/j.issn.1000?436x.2018276
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    A new routing algorithm MIEBR(message importance based energy balanced routing algorithm) was proposed. MIEBR measures the importance of messages. It determines message forwarding order and routing by message forwarding profit. When cache space is insufficient, MIEBR performs cache replacement based on message cache value. Simulation results show that, in cache space and energy constrained networks, MIEBR balances energy consumption of nodes, and reduces the latency of important messages. It outperforms other algorithms in delivery rate and latency.

    Cross-domain service chain mapping mechanism based on Q-learning
    Hongqi ZHANG,Rui HUANG,Yingjie YANG,Dexian CHANG,Liancheng ZHANG
    2018, 39(12):  102-112.  doi:10.11959/j.issn.1000-436x.2018283
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    A virtual service resources controlling architecture with regional centralized management and global coordinated scheduling was proposed for the problem of cross-domain service chain mapping in SDNFV environment. On this basis, an effective mapping framework was built and the cross-domain mapping problem was modeled as an ILP with the purpose of minimizing mapping cost. A partitioning algorithm was designed to solve the problem based on Q-learning mechanism under this framework. Simulation results show that the performances of this method are better than other traditional methods on average partition time, average mapping cost, and acceptance ratioof service chain mapping request.

    k-times attribute-based authentication scheme using direct anonymous attestation
    Xin LIU,Qiuliang XU,Bin ZHANG,Bo ZHANG
    2018, 39(12):  113-133.  doi:10.11959/j.issn.1000-436x.2018279
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    s: At present, the main drawbacks of existing k-times attribute-based authentication (abbreviated to k-TABA) schemes and related attribute-based authentication schemes are that the computation cost of the authentication process depends on the size of the access formula and none of these schemes considers the problems of member revocation and attribute update. A new k-TABA scheme was constructed based on the building blocks of direct anonymous attestation, set membership proof and ciphertext-policy attribute-based encryption. Moreover, in order to reduce user's calculation as much as possible, the underlying attribute-based encryption scheme was modified, and then the main decryption operations were outsourced by using the key binding technique of Green et al. The new scheme can be deployed on a trusted platform and support expressive authentication policies. In addition, it also satisfies several ideal properties, such as registration process verifiability, member revocation, attribute update, and so on. The significant performance advantage of the new scheme is that the computation overhead of the user in the authentication phase is constant.

    Comprehensive Review
    Industrial intelligent network: deepening and upgrading of industrial Internet
    Ping ZHANG,Huiyong LIU,Wenjing LI,Fanqin ZHOU
    2018, 39(12):  134-140.  doi:10.11959/j.issn.1000-436x.2018292
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    Manufacturing founds a major pillar of the national economy. The international community generally agrees that the core of the new wave of manufacturing upgrade is to achieve intelligent manufacturing. For this reason, the concepts of “Industrial Internet” and “Industry 4.0” was proposed by united state, Germany and other technologied, and formulated manufacturing development strategies suited to their national conditions. “Made in China 2025” was proposed by China which determines the development direction based on intelligent manufacturing in the level of national development strategy. Based on the status quo and technological advantages of China's industrial intelligent manufacturing, and aiming to help large, medium and small-sized production enterprises achieve industrial intelligence in a flexible, smooth and cost-controllable manner, the concept of “industrial intelligent network” was proposed to integrate the conditions and advantages in aspects of China's information infrastructure construction, cognitive identification, artificial intelligence, etc., to build an industrial intelligent network, to provide industrial intelligent services to large, medium and small-sized enterprises, so that production enterprises within a broader scale can benefit from intelligent manufacturing with lower costs.

    Correspondences
    Study on user behavior profiling in insider threat detection
    Yuanbo GUO,Chunhui LIU,Jing KONG,Yifeng WANG
    2018, 39(12):  141-150.  doi:10.11959/j.issn.1000-436x.2018282
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    Behavior profiling technic using no-labeled historical data to build normal behavior model is an effective way to detect insider attackers. The state-of-the-art labeled profile methods extract features artificially and process data by simple statistical methods, whose incomplete behavior model lacks details. An automated feature extracting and full-detail behavior profiling method as well as a behavior sequence splitting and business state transition predicting way was proposed. Combining above two methods, an insider threats detection framework was established, which improved detection accuracy. Experimenting with CMU-CERT data set, AUC (area under curve) score was 0.88 and F1 score was 0.925. With the better performance, it can be used in detecting insider threats.

    Study on Chinese spam filtering system based on Bayes algorithm
    Haoran LIU,Pan DING,Changjiang GUO,Jinfeng CHANG,Jingchuang CUI
    2018, 39(12):  151-159.  doi:10.11959/j.issn.1000?436x.2018281
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    In view of the shortcoming that high dimension of features in the Chinese spam filtering system, a TF-IDF features extraction algorithm was proposed based on the central word extension, the algorithm improves the expression capacity of the node in the network and reduces the dimension of feature. Further, a three-layer structure model based on GWO_GA structure learning algorithm was proposed to expand the limit of text features and improve the diversity of text features. The new structure learning algorithm relaxes the conditional independence assumption of feature properties. A fine classification layer was added between class layer and feature layer to increase feature coverage. The experiment demonstrates that the three-layer Bayesian network algorithm with TF-IDF feature extraction based on the central word extension and GWO_GA structure learning improves the effect of Chinese spam filtering.

    Non-coherent demodulation algorithm of MSK based on differential composite
    Wenbiao TIAN,Peng WANG,Guosheng RUI,Yang ZHANG
    2018, 39(12):  160-166.  doi:10.11959/j.issn.1000?436x.2018278
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    An algorithm of MSK demodulation based on differential composite grid was proposed. The MSK differential composite grid was constructed by phase deflection, and the optimal path in the composite grid was selected by comparing the likelihood function value to compensate the phase error of the Doppler frequency offset. Theoretical analysis and simulation show that the performance of the algorithm was still close to the theoretical lower bound of the MSK non-coherent demodulation error rate when the phase error caused by the Doppler frequency offset was of the order of 10? 1rad magnitude. The algorithm extends the range of MSK demodulation anti-Doppler frequency offset, and is superior to similar algorithm in complexity and decision delay time, slightly higher than 1 symbol differential algorithm corresponding value, which provides a new means for demodulation of MSK under Doppler frequency offset.

    Radio tomographic imaging localization method based on the improved ellipse weight model
    Li LI,Wei KE,Hengkuan XU,Kunliang YU,Yanli WANG
    2018, 39(12):  167-174.  doi:10.11959/j.issn.1000?436x.2018290
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    As one of the main methods of device free localization (DFL), the radio tomographic imaging (RTI) method that can locate a target without attaching any devices has wide application prospects. To overcome the shortcoming of the existing ellipse weight model, based on the Fresnel diffraction theory an improved ellipse weight model was proposed to enhance the imaging quality of RTI and demonstrates the feasibility of this model. Meanwhile, a foreground detection algorithm based on the cross model was proposed to reduce the impact of background noises and pseudo-targets, thereby further improving the imaging quality. The indoor and outdoor experimental results verify that the imaging quality and the positioning accuracy of the proposed method are better than the existing RTI methods.

Copyright Information
Authorized by: China Association for Science and Technology
Sponsored by: China Institute of Communications
Editor-in-Chief: Zhang Ping
Associate Editor-in-Chief:
Zhang Yanchuan, Ma Jianfeng, Yang Zhen, Shen Lianfeng, Tao Xiaofeng, Liu Hualu
Editorial Director: Wu Nada, Zhao Li
Address: F2, Beiyang Chenguang Building, Shunbatiao No.1 Courtyard, Fengtai District, Beijing, China
Post: 100079
Tel: 010-53933889、53878169、
53859522、010-53878236
Email: xuebao@ptpress.com.cn
Email: txxb@bjxintong.com.cn
ISSN 1000-436X
CN 11-2102/TN
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