[1] 赵国庆. 雷达对抗原理[M]. 2版. 西安: 西安电子科技大学出版社, 2012: 87- 105.

    Zhao GQ. Principle radar countermeasure[M]. 2nd ed. Xi'an: Xi'an University of Electronic Science and Technology Press, 2012: 87- 105.

[2] 杨发权, 李赞, 罗中良. 混合调制信号调制识别方法[J]. 中山大学学报(自然科学版), 2014, 53(1): 42-46.

    Yang F Q, Li Z, Luo Z L. Method of modulation recognition of mixed modulation signal[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2014, 53(1): 42-46.

[3] 朱斌. 雷达辐射源信号特征提取与评价方法研究[D]. 成都: 西南交通大学, 2015: 17- 24.

    ZhuB. Study on feature extraction and evaluation method of radar emitter signals[D]. Chengdu: Southwest Jiaotong University, 2015: 17- 24.

[4] Zhang W X, Sun F L, Wang B. Radar signal intra-pulse feature extraction based on improved wavelet transform algorithm[J]. International Journal of Communications, Network and System Sciences, 2017, 10(8): 118-127.

[5] 符颖, 王星, 周东青, 等. 基于模糊函数SVD和改进S3VM的雷达信号识别[J]. 计算机工程与应用, 2017, 53(6): 264-270.

    Fu Y, Wang X, Zhou D Q, et al. Recognition method of radar signal based on SVD of ambiguity function and improved S3VM algorithm[J]. Computer Engineering and Applications, 2017, 53(6): 264-270.

[6] 高玮玮, 沈建新, 王玉亮, 等. 改进的快速FCM及SVM实现糖网白色病灶的自动检测[J]. 中国生物医学工程学报, 2013, 32(3): 305-312.

    Gao W W, Shen J X, Wang Y L, et al. Automated detection of bright lesions of diabetic retinopathy based on improved and fast FCM and SVM[J]. Chinese Journal of Biomedical Engineering, 2013, 32(3): 305-312.

[7] 吴剑旗, 田西兰. 一种基于半监督学习的窄带雷达目标识别系统[J]. 中国电子科学研究院学报, 2015, 10(1): 49-53.

    Wu J Q, Tian X L. Anarrow-band radar target recognition system based on semi-supervised learning[J]. Journal of China Academy of Electronics and Information Technology, 2015, 10(1): 49-53.

[8] Breiman L. Random forest[J]. Machine Learning, 2001, 45(1): 5-32.

[9] 赵克勤. 偏联系数[C]∥中国人工智能进展2005论文集. 北京: 北京邮电大学出版社, 2005, 6: 884- 885.

    Zhao KQ. Partial connection number [C]∥Proceedings of Chinese Artificial Intelligence 2005.Beijing: Beijing University of Posts and Telecommunications Press, 2005, 6: 884- 885.

[10] Rao R V, Savsani V J, Vakharia D P. Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems[J]. Computer-Aided Design, 2011, 43(3): 303-315.

[11] 黎蓉, 刘以安, 王刚. 基于改进集对分析聚类的雷达信号分选方法[J]. 现代电子技术, 2014, 37(9): 8-11.

    Li R, Liu Y A, Wang G. Radar signal sorting method based on modified set pair analysis clustering[J]. Modern Electronics Technique, 2014, 37(9): 8-11.

[12] 张秀辉, 刘以安, 曹宁生, 等. 基于集对分析的雷达信号分选算法[J]. 现代雷达, 2010, 32(2): 35-37.

    Zhang X H, Liu Y A, Cao N S, et al. Radar signal sorting method based on set pair analysis[J]. Modern Radar, 2010, 32(2): 35-37.

[13] 张永库, 尹灵雪, 孙劲光. 基于改进的遗传算法的模糊聚类算法[J]. 智能系统学报, 2015, 10(4): 627-635.

    Zhang Y K, Yin L X, Sun J G. Fuzzy clustering algorithm based on the improved genetic algorithm[J]. CAAI Transactions on Intelligent Systems, 2015, 10(4): 627-635.

[14] 李大威, 杨风暴, 王肖霞. 基于随机森林与D-S证据合成的多源遥感分类研究[J]. 激光与光电子学进展, 2016, 53(3): 031001.

    Li D W, Yang F B, Wang X X. Multisource remote sensing classification based on random forest and adaptive weighted D-S evidence synthesis[J]. Laser & Optoelectronics Progress, 2016, 53(3): 031001.

[15] 孔清清, 丁香乾, 宫会丽. 改进的修剪随机森林算法在烟叶近红外光谱产地识别中的应用研究[J]. 激光与光电子学进展, 2018, 55(1): 013006.

    Kong Q Q, Ding X Q, Gong H L. Application of improved random forest pruning algorithm in tobacco origin identification of near infrared spectrum[J]. Laser & Optoelectronics Progress, 2018, 55(1): 013006.

[16] 蔡加欣, 冯国灿, 汤鑫, 等. 基于局部轮廓和随机森林的人体行为识别[J]. 光学学报, 2014, 34(10): 1015006.

    Cai J X, Feng G C, Tang X, et al. Human action recognition based on local image contour and random forest[J]. Acta Optica Sinica, 2014, 34(10): 1015006.

[17] 徐军辉, 王艳. 基于改进教与学算法的离散制造车间能效优化[J]. 系统仿真学报, 2016, 28(12): 3019-3026.

    Xu J H, Wang Y. Energy efficiency optimization for discrete manufacturing workshop based on discrete teaching-learning-based optimization algorithm[J]. Journal of System Simulation, 2016, 28(12): 3019-3026.

[18] 李靖超. 基于三维熵特征的雷达信号识别[J]. 上海电机学院学报, 2015, 18(3): 136-140.

    Li J C. Radar signal recognition based on three dimensional entropy features[J]. Journal of Shanghai Dianji University, 2015, 18(3): 136-140.

[19] 刘凯, 韩嘉宾, 黄青华. 基于改进相像系数和奇异谱熵的雷达信号分选[J]. 现代雷达, 2015, 37(9): 80-85.

    Liu K, Han J, Huang Q H. Sorting radar signal based on the improved resemblance coefficient and singular spectrum entropy[J]. Modern Radar, 2015, 37(9): 80-85.