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机器智能研究（英文）
机器智能研究（英文）

谭铁牛　刘国平　胡豁生

双月刊

2731-538X

ijac@ia.ac.cn

010-62655893

100190

北京海淀区中关村东路95号2728信箱

机器智能研究（英文）/Journal Machine Intelligence ResearchCSCDCSTPCD北大核心EI
查看更多>>International Journal of Automation and computing is a publication of Institute of Automation, the Chinese Academy of Sciencs and Chinese Automation and computing Society in the United Kingdom. The Journal publishes papers on original theoretical and experimental research and development in automation and computing. The scope of the journal is extensive. Topics include; artificial intelligence, automatic control, bioinformatics, computer sciene, information technology, modeling and simulation, networks and communications, optimization and decision, pattern recognition, robotics, signal processing, and systems engineering.
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    Optimal Strategy for Aircraft Pursuit-evasion Games via Self-play Iteration

    Xin WangQing-Lai WeiTao LiJie Zhang...
    585-596页
    查看更多>>摘要：In this paper,the pursuit-evasion game with state and control constraints is solved to achieve the Nash equilibrium of both the pursuer and the evader with an iterative self-play technique.Under the condition where the Hamiltonian formed by means of Pontryagin's maximum principle has the unique solution,it can be proven that the iterative control law converges to the Nash equilibri-um solution.However,the strong nonlinearity of the ordinary differential equations formulated by Pontryagin's maximum principle makes the control policy difficult to figured out.Moreover the system dynamics employed in this manuscript contains a high dimension-al state vector with constraints.In practical applications,such as the control of aircraft,the provided overload is limited.Therefore,in this paper,we consider the optimal strategy of pursuit-evasion games with constant constraint on the control,while some state vectors are restricted by the function of the input.To address the challenges,the optimal control problems are transformed into nonlinear pro-gramming problems through the direct collocation method.Finally,two numerical cases of the aircraft pursuit-evasion scenario are giv-en to demonstrate the effectiveness of the presented method to obtain the optimal control of both the pursuer and the evader.
      原文链接:
    • NETL
    • NSTL
    • 万方数据

    Enhance the Performance of Directional Feature-based Palmprint Recognition by Directional Response Stability Measurement

    Haitao WangWei Jia
    597-614页
    查看更多>>摘要：Palmprint recognition is an emerging biometrics technology that has attracted increasing attention in recent years.Many palmprint recognition methods have been proposed,including traditional methods and deep learning-based methods.Among the tradi-tional methods,the methods based on directional features are mainstream because they have high recognition rates and are robust to il-lumination changes and small noises.However,to date,in these methods,the stability of the palmprint directional response has not been deeply studied.In this paper,we analyse the problem of directional response instability in palmprint recognition methods based on dir-ectional feature.We then propose a novel palmprint directional response stability measurement(DRSM)to judge the stability of the directional feature of each pixel.After filtering the palmprint image with the filter bank,we design DRSM according to the relationship between the maximum response value and other response values for each pixel.Using DRSM,we can judge those pixels with unstable directional response and use a specially designed encoding mode related to a specific method.We insert the DRSM mechanism into sev-en classical methods based on directional feature,and conduct many experiments on six public palmprint databases.The experimental results show that the DRSM mechanism can effectively improve the performance of these methods.In the field of palmprint recognition,this work is the first in-depth study on the stability of the palmprint directional response,so this paper has strong reference value for re-search on palmprint recognition methods based on directional features.
      原文链接:
    • NETL
    • NSTL
    • 万方数据