网站导航网学 原创论文 原创专题 网站设计 最新系统 原创论文 论文降重 发表论文 论文发表 UI设计定制 论文答辩PPT格式排版 期刊发表 论文专题
返回网学首页
网学原创论文
最新论文 推荐专题 热门论文 论文专题
当前位置: 网学 > 论文模板 > 毕业论文参考文献 > 正文

本科计算机安全论文参考文献(准确引用80个)

论文降重修改服务、格式排版等 获取论文 论文降重及排版 论文发表 相关服务

网学网为广大网友收集整理了,本科计算机安全论文参考文献(准确引用80个),希望对大家有所帮助!

毕业论文(paper)里面的参考文献怎么写?随便粘贴复制可以吗?当然不可以!小编整理了关于计算机安全论文(paper)类目下的参考文献80篇,敬请笑纳!

计算机安全论文(paper)参考文献一

[1] 李子青. 人脸识别技术应用和市场分析[J]. 中国安防, 2007, 8: 42-46.

[2] Zhao W, Chellappa R, Phillips P J, et al. Face recognition: a literature survey[J]. ACM Computing Surveys, 2003, 35 (4): 399-458.

[3] 李晓东. 人脸识别算法研究[D]. 南京:东南大学, 2009.

[4] 黄非非. 基于LBP的人脸识别研究[D]. 重庆:重庆大学, 2009.

[5] Guan S , Li X. Improved maximum scatter difference discriminant analysis for face recognition[J]. Measurement and Control, 2009: 368-371.

[6] Bledsoe W W. Man-machine facial recognition[M]. Palo Alto: Panoramic Research Incorporation, 1966: 1-20.

[7] Yang C, Shi S, Li L, et al. Face recognition with single training sample based on local feature fusion[A]. // Tenth International Symposium on Distributed Computing and Applications to Business, Engineering and Science[C], Wuxi: IEEE, 2012: 165-169.

[8] 赵汝哲, 房斌, 文静. 自适应加权LBP的单样本人脸识别算法[J]. 计算机工程与应用, 2012, 48(31): 146-149.

[9] 杨秀坤, 岳新启, 汲清波. 基于HOG和DMMA的单样本人脸识别[J]. 计算机应用研究, 2015, 2: 627-629.

[10] Kan M, Shan S, Su Y, et al. Adaptive discriminant learning for face recognition[J]. Pattern Recognition, 2013, 46(9): 2497-2509.

[11] Wang J, Plataniotis K N, Lu J, et al. On solving the face recognition problem with one training sample per subject[J]. Pattern Recognition, 2006, 39(9): 1746-1762.

[12] Majumdar A, Ward R K. Pseudo-Fisherface method for single image per person face recognition[A]. // IEEE International Conference on Acoustics, Speech and Signal Processing[C], Las Vegas: IEEE, 2008: 989-992.

[13] Kim T K, Kittler J. Locally linear discriminant analysis for multimodally distributed classes for face recognition with a single model image[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2012, 27(3):318-327.

[14] Kirby M, Sirovich L. Application of the KL procedure for the characterization of human faces[J]. IEEE Trans. Pattern Mach. Intell, 1990, 12 (1): 103-108.

[15] Huang J, Yuen P C, Chen W S, et al. Component-based LDA method for face recognition with one training sample[A]. // IEEE International Workshop on Analysis and Modeling of Faces and Gestures[C]. Nice: IEEE, 2003:120-126.

[16] Gao Q X, Zhang L, Zhang D. Face recognition using FLDA with single training image per person[J]. Applied Mathematics & Computation, 2008, 205(2): 726-734.

[17] Ko? M, Barkana A. A new solution to one sample problem in face recognition using FLDA[J]. Applied Mathematics & Computation, 2011, 217(24): 10368-10376.

[18] Hu C, Ye M, Ji S, et al. A new face recognition method based on image decomposition for single sample per person problem[J]. Neurocomputing, 2015, 160(C):287-299.

[19] Jing X Y, Zhang D, Tang Y Y. An improved LDA approach[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B(Cybernetics), 2004, 34(5):1942-1951.

[20] Ye J, Janardan R, Li Q. Two-dimensional linear discriminant analysis[J]. Photogrammetric Engineering and Remote Sensing, 2004, 5: 1431-1441.

[21] Li M, Yuan B. 2D-LDA: A statistical linear discriminant analysis for image matrix[J]. Pattern Recognition Letters, 2005, 26: 527-532.

[22] Golub G H, Van Loan C F. Matrix computations[M]. Baltimore: Johns Hopkins University Press, 1996.

[23] 张志涌, 杨祖樱. MATLAB教程[M]. 北京: 北京航空航天大学出版社, 2015.

[24] Samaria F S, Harter A C. Parameterisation of a stochastic model for human face identification[A]. // Applications of Computer Vision[C], Sarasota: Proceedings of the Second IEEE Workshop on, IEEE, 1994:138-142.

[25] Phillips P J, Moon H H, Rizvi S A, Rauss P J. The FERET evaluation methodology for face-recognition algorithms[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22: 1090-1104.

[26] Martinez A M. The AR face database[R]. Computer Vision Center Technical Report, 1998, 24.

计算机安全论文(paper)参考文献二

[27] 陈景藻. 康复医学. 北京: 高等教育出版社, 2001.

[28] 祁奇,郁嫣嫣,屠霞芬等. 社区及家庭康复指导对脑卒中患者日常生活活动能力的影响[J]. 中国康复医学杂志, 2009 (11): 1021-1023.

[29] 何祥,韩丹. 脑卒中后神经康复治疗机制的研究进展[J]. 中国临床康复, 2003: 2722-2723.

[30] 张小丽,齐瑞,严隽陶.中风后偏瘫中西医结合优化康复方案的临床研究[J].中国针灸,2013,33(12): 1113-1117.

[31] Nef. T, Riener. R. Shoulder actuation mechanisms for arm rehabilitation exoskeletons. In Biomedical Robotics and Biomechatronics, BioRob 2008. 2nd IEEE RAS &EMBS International Conference on, 2008; 862-868.

[32] J. Ma, Study on surface EMG analysis methods under rehabilitation exercise[D], Qinhuangdao,Yanshan University,2015

[33] Zecca, M.,Micera, S.,Carrozza, M., et al. Control of multifunctional prosthetic hands by processing the electromyographic signal. Critical Reviews? in Biomedical Engineering, 2002, 30 (4-6).

[34] Nef T.,Mihelj M.,Riener R. ARMin: a robot for patient-cooperative arm therapy. Medical & biological engineering & computing, 2007, 45 (9): 887-900.

[35] Nef T.,Guidali M.,Riener R. ARMin III–arm therapy exoskeleton with an ergonomic shoulder actuation. Applied Bionics and Biomechanics, 2009, 6 (2): 127-142.

[36] Perry J. C.,Rosen J.,Burns S. Upper-limb powered exoskeleton design. Mechatronics, IEEE/ASME Transactions on, 2007, 12 (4): 408-417.

[37] Perry J. C.,Powell J. M.,Rosen J. Isotropy of an upper limb exoskeleton and the kinematics and dynamics of the human arm. Applied Bionics and Biomechanics, 2009,6 (2): 175-191.

[38] Kiguchi K, Hayashi Y. A study of EMG and EEG during perception-assist with an upper-limb power-assist robot[C]. Robotics and Automation (ICRA), 2012 IEEE International Conference on. IEEE, 2012: 2711-2716.

[39] Bitzer S, van der Smagt P. Learning EMG control of a robotic hand: towards active prostheses[C]. Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on. IEEE, 2006: 2819-2823.

[40] 杨大鹏,赵京东,姜力等. 一种3自由度仿人型假手的肌电控制[J].江苏大学学报:自然科学版,2009,30(1):5-9.

[41] 姚鹏飞. 基于表面肌电信号与近红外光谱技术联合解码的仿人假肢控制系统,2015年,上海交通大学硕士学位论文(paper).

[42] 罗志增,王人成. 基于表面肌电信号的前臂手部多运动模式识别[J]. 仪器仪表学报, 2006: 74-78.

[43] 罗志增,马文杰,孟明. 一种基于HHT和AR模型的手部运动模式识别方法[J]. 模式识别与人工智能, 2008,21(2):227-232

[44] 张启忠,席旭刚,罗志增. 基于表面肌电信号形态特征的多模式识别研究. 传感技术学报,2012,25(12):1636-1642

[45] Micera S., Sabatini A. M., Dari, P., et al. A hybrid approach to EMG pattern analysis for classification of arm movements using statistical and fuzzy techniques. Medical engineering & physics, 1999, 21 (5): 303-311.

[46] Guanglin Li. Quantifying Pattern Recognition—Based Myoelectric Control of Multifunctional Transradial Prostheses. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2010

[47] Hyun K. Kim,Byungduk K. Estimation of Multijoint Stiffness Using Electromyogram and Artificial Neural Network, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL.39,NO.5,2009

[48] HOGAN N.Impedance control: an approach to manipulation[J]. Journal of Dynamic Systems,Measurement and Control,1985,107:1-24.

[49] MUSSA-IVALDI F A,HOGAN N,BIZZI E.Neural mechanical and geometric factors subserving arm posture in humans[J]. Journal of Neuroscience,1985,5(10):2732-2743.

[50] Ajoudani A, Tsagarakis N, Bicchi A. Tele-impedance: tele-operation with impedance regulation using a body-machine interface. International Journal of Robotics Research, 2012,31(13):1642?1656

[51] 丁其川,熊安斌,赵新刚,等.基于表面肌电的运动意图识别方法研究及应用综述[J].自动化学报,2016,42(1):13-25.

[52] Liang P D, Yang C G, et al. Implementation and test of human-operated and human-like adaptive impedance controls on Baxter robot. Advances in Autonomous Robotics Systems. Switzerland: Springer In-ternational Publishing, 2014. 109?119

[53] 吴丹青,周昌乐. 小波变换的计算机实现[J]. 计算机应用与软件,2005,22(5):8-10

[54] 邱青菊. 表面肌电信号的特征提取与模式分类研究[D]. 上海:上海交通大学,2009

[55] 张坤. 表面肌电信号识别和分类的研究[D]. 上海:上海交通大学,2009

[56] Ray G C, Guha S K. Relationship between the surface EMG and muscular force[J]. Medical & Biological Engineering & Computing, 1983, 21(5): 579-586.

[57] Nandedkar S D, Sanders D B, St?lberg E V, et al. Simulation of concentric needle EMG motor unit action potentials[J]. Muscle & Nerve, 1988, 11(2): 151-9.

[58] HILL A V.The heat of shortening and the dynamic constants of muscle[J].Proceedings of the Royal Society B: Biological Sciences,1938,126( 843) : 136-195.

[59] Lloyd D G,BesieR TF.An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo[J]. Journal of Biomechanics, 2003,36( 6) : 765-776.

[60] KIM H K,KANG B,KIM B,et al.Estimation of multijoint stiffness using electromyogram and artificial neural network[J]. IEEE Transactions on Systems Man and Cybernetics,Part A: Systems and Humans,2009,39( 5) : 972-980.

计算机安全论文(paper)参考文献三

[61] Agrawal R, Faloutsos C, Swami A N. Efficient similarity search in sequence databases[A]. // Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms [C], Berlin: Springer-Verlag, 1993: 69-84.

[62] Poiker T, Douglas D H. Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature[J]. Classics in Cartography, 1973, 10(2): 112-122.

[63] 李慧. 奇异值分解在时间序列分析中的应用[D]. 北京: 北京交通大学, 2009.

[64] Potamias M, Patroumpas K, Sellis T. Sampling trajectory streams with spatiotemporal criteria[A]. // 18th International Conference on Scientific and Statistical Database Management[C], Vienna: IEEE, 2006: 275-284.

[65] Kim S W, Park S, Chu W W. An index-based approach for similarity search supporting time warping in large sequence databases[A]. // 17th International Conference on Data Engineering[C], Heidelberg: IEEE, 2001: 607-614.

[66] Yi B K, Jagadish H V, Faloutsos C. Efficient retrieval of similar time sequences under time warping[A]. // 14th International Conference on Data Engineering[C], Orlando: IEEE, 1998: 201-208.

[67] Keogh E, Ratanamahatana C A. Exact indexing of dynamic time warping[J]. Knowledge and Information Systems, 2005, 7(3): 358-386.

[68] Zhu Y, Shasha D. Warping indexes with envelope transforms for query by humming[A]. // Proceedings of the 2003 ACM SIGMOD international conference on Management of data[C], San Diego: ACM, 2003: 181-192.

[69] Zheng Y, Zhang L, Xie X, et al. Mining interesting locations and travel sequences from GPS trajectories[A]. // Proceedings of the 18th international conference on World wide web[C], Madrid: ACM, 2009: 791-800.

[70] Zheng Y, Li Q, Chen Y, et al. Understanding mobility based on GPS data[A]. // Proceedings of the 10th international conference on Ubiquitous computing[C], Seoul: ACM, 2008: 312-321.

[71] Zheng Y, Xie X, Ma W Y. GeoLife: A collaborative social networking service among user, location and trajectory[J]. IEEE Bulletin of the Technical Committee on Data Engineering, 2011, 33(2): 32-39.

[72] Douglas D H, Peucker T K. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature[J]. Canadian Cartographer, 1973, 10(2): 112-122.

[73] 孙兴春, 何文斌. 一种Douglas-Peucker加速算法[J]. 科技信息, 2009, 20: 202-203.

[74] 熊英志. 时间序列的特征表示与聚类方法研究[D]. 重庆:重庆大学, 2016.

[75] 张达夫, 张昕明. 基于时空特性的GPS轨迹数据压缩算法[J]. 交通信息与安全, 2013, 31(3): 6-9.

[76] Keogh E, Wei L, Xi X, et al. LB_Keogh supports exact indexing of shapes under rotation invariance with arbitrary representations and distance measures[A]. // Proceedings of the 32nd international conference on Very large data bases[C], Seoul: VLDB Endowment, 2006: 882-893.

[77] Lemire D. Faster retrieval with a two-pass dynamic-time-warping lower bound[J]. Pattern Recognition, 2009, 42(9): 2169-2180.

[78] Vlachos M, Kollios G, Gunopulos D. Discovering similar multidimensional trajectories[A]. // 18th International Conference on Data Engineering[C], San Jose: IEEE, 2002: 673-684.

[79] Chen L, ?zsu M T, Oria V. Robust and fast similarity search for moving object trajectories[A]. // Proceedings of the 2005 ACM SIGMOD international conference on Management of data[C], Baltimore: ACM, 2005: 491-502.

[80] Procopiuc O, Agarwal P K, Arge L, et al. Bkd-Tree: A Dynamic Scalable kd-Tree[J]. Advances in Spatial and Temporal Databases, 2003:46-65.

设为首页 | 加入收藏 | 网学首页 | 原创论文 | 计算机原创
版权所有 网学网 [Myeducs.cn] 您电脑的分辨率是 像素
Copyright 2008-2020 myeducs.Cn www.myeducs.Cn All Rights Reserved 湘ICP备09003080号 常年法律顾问:王律师