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杨利军BEVITOR伟德505房间
姓名:杨利军
职称:副教授
办公室:BEVITOR伟德308室
邮箱: yanglijun@henu.edu.cn
研究方向:智能信息处理
教育背景:
2010.09-2013.06, 博士, 中山大学, 信息计算科学专业
2002.09-2005.07, 硕士, BEVITOR伟德APP官网, 应用数学专业
1998.09-2002.07, 学士, BEVITOR伟德APP官网, 数学教育专业
工作经历:
2016.12-至今, BEVITOR伟德APP官网, 副教授
2018.07-2019.07, 佐治亚理工学院, 访问学者
2008.07-2016.12, BEVITOR伟德APP官网, 讲师
2005.07-2008.07, BEVITOR伟德APP官网, 助教
科研项目:
1) EEG脑功能网络分析及其在抑郁症辅助识别中的应用(编号212102310305),河南省重点研发与推广专项(科技攻关)项目,2021.01-2022.12,10万元,在研,主持;
2) 经验模态分解的关键理论和应用研究(编号11701144),国家自然科学基金青年基金项目,2018.01-2020.12, 20万元,结题,主持;
3) 信号时频分析与包络的数学模型(编号11426087),数学天元基金项目,2015.01-2015.12,3万元,结题,主持;
4) 经验模态分解的理论和应用研究,河南省高等学校青年骨干教师培养计划(编号2017GGJS020),2018.01-2020.12,3万元,主持;
5) 单分量信号模型与信号自适应稀疏分解算法研究(编号16A120002),河南省教育厅科学技术研究重点项目,2016.01-2017.12,3万元,结题,主持;
6) 包络的理论、算法及单分量信号研究(编号2013YBZR016),BEVITOR伟德APP官网科研基金项目,2014.01-2015.12,1万元,结题,主持;
7) 高维半参数回归统计优化模型的基本性质及算法(编号11971149),国家自然科学基金面上项目,2020/01-2023/12,52万元,在研,参与;
8) 几类典型稀疏优化问题的算法、理论及应用(编号11471101),国家自然科学基金面上项目,2015.01-2018.12,56万元,结题,参与;
9) 基于多尺度几何分析和SVM的Web图像检索技术研究(编号60802061),国家自然科学基金青年基金项目,2009.01- 2011.12,18万元,结题,参与.
主讲课程:
信号与系统;模式识别与图像处理;高等数学
社会兼职:
中国工业与应用数学学会会员;河南省数字图形图像学会会员
期刊论文:
1)Lijun Yang*, Yixin Wang, Xiangru Zhu and Xiaohui Yang, A Gated Separable- Temporal Attention Network for EEG-Based Depression Recognition, Computers in Biology and Medicine, 157(2023) 106782.
2)Lijun Yang*, Yixin Wang, Xiaohui Yang, and Chen Zheng, Stochastic Weight Averaging Enhanced Temporal Convolution Network for EEG-based Emotion Recognition, Biomedical Signal Processing and Control, 83 (2023) 104661.
3)Lijun Yang, Xiaoge Wei, Fengrui Liu, Xiangru Zhu, Feng Zhou*, Automatic feature learning model combining functional connectivity network and graph regularization for depression detection, Biomedical Signal Processing and Control, 82 (2023) 104520.
4)Lijun Yang, Lulu Yan, Xiaoge Wei and Xiaohui Yang*, Label consistency-based deep semisupervised NMF for tumor recognition, Engineering Applications of Artificial Intelligence, 117 (2023) 105511.
5)Lijun Yang*, Shuyue Jiang, Xiaoge Wei and Yunhai Xiao, EEG feature learning model based on intrinsic time-scale decomposition and adaptive Huber loss, Chinese Quarterly Journal of Mathematics, 37(3): 281-300, 2022.
6)Lijun Yang, Lulu Yan, Xiaohui Yang*, Xin Xin and Liugen Xue, Bayesian Nonnegative Matrix Factorization in an Incremental Manner for Data Representation, Applied Intelligence, Accepted, 2022. DOI:https://doi.org/10.1007/s10489-022-03522-3.
7)Lijun Yang*, Sijia Ding, Feng Zhou, Xiaohui Yang and Yunhai Xiao, Robust EEG feature learning model based on an adaptive weight and pairwise-fused LASSO, Biomedical Signal Processing and Control, 68:102728, 2021.
8)王怡忻,朱湘茹,杨利军*,融合共空间模式与脑网络特征的EEG抑郁识别,计算机工程与应用,2022, v.58; No.1013(22) 150-158.
9)Qun Zhang, Lijun Yang and Feng Zhou*, Attention enhanced long short-term memory network with multi-source heterogeneous information fusion: An application to BGI Genomics, Information Sciences, 553:305-330, 2021.
10)Lijun Yang*, Shuang Li, Zhi Zhang, Xiaohui Yang, Classification of Phonocardiogram signals based on envelope optimization model and support vector machine, Journal of Mechanics in Medicine and Biology, 20(1):1950062, 2020.
11)Lijun Yang*, Sijia Ding, Hao Min Zhou and Xiaohui Yang, A strategy combining intrinsic time-scale decomposition and feedforward neural network for automatic seizure detection, Physiological Measurement, 40 (9) 095004, 2019.
12)Feng Zhou, Lijun Yang, Haomin Zhou and Lihua Yang. Optimal Averages for Nonlinear Signal Decompositions—Another Alternative for Empirical Mode Decomposition. Signal Processing, 2016, 121:17-29.
13)Lijun Yang, Chao Huang and Zhihua Yang. The Model and Construction of Weak-IMFs. Computational & Applied Mathematics, 2015, 34(2):661-670.
14)Lijun Yang, Zhihua Yang and Lihua Yang*. The theoretical analysis for an iterative envelope algorithm. Digital Signal Processing, 2015, 38:32-42.
15)Chao Huang, Lijun Yang and Lihua Yang. ϵ-Mono-component: its Characterization and Construction, IEEE Transactions on Signal Processing, 2015, 63(1):234-243.
16)Xiaohui Yang, Jingjing Liu and Lijun Yang*. Product Image Classification Based on Fusion Feature. Chinese Quarterly Journal of Mathematics, 2015, 30(3):429-441.
17)Lijun Yang, Zhihua Yang, Feng Zhou and Lihua Yang. A Novel Envelope Model Based On Convex Constrained Optimization. Digital Signal Processing, 2014, 29:138-146.
会议论文:
1)Xiaoge Wei, Shengnan Liu, Lijun Yang*, Supervised nonnegative matrix factorization model with fused correntropy for tumor recognition. The Second International Conference on Image, Signal Processing and Pattern Recognition (ISPP 2023).
2)Rujie Ou Yang, Shengnan Liu, Lijun Yang*, EEG emotion recognition based on graph signal and stable learning, The 2nd international conference on computational modeling, simulation and data analysis (CMSDA 2022).
3)Xiaolong Niu, Xingyu Zhang, Lijun Yang*, MI-EEG Recognition Based on Euclidean Alignment and Style Transfer Mapping, The 2nd international conference on computational modeling, simulation and data analysis (CMSDA 2022).
4)Yixin Wang, Fengrui Liu, Lijun Yang*, EEG-Based Depression Recognition Using Intrinsic Time-scale Decomposition and Temporal Convolution Network, The Fifth International Conference on Biological Information and Biomedical Engineering (BIBE2021).
专利、软著:
1)基于小波变换和全变差正则化的信号去噪方法,中华人民共和国发明专利,授权公告号:CN111657936B,授权公告日:2022.04.12.
2)抑郁症辅助诊断系统v1.0,计算机软件著作权登记证书,登记号:2022SR0577236. 2022年
3)基于小波包分解的迭代阈值去噪系统V1.0,计算机软件著作权登记证书,登记号:2021SR0509851. 2021年
4)基于ITD和改进的MFCC的心音信号识别系统V1.0,计算机软件著作权登记证书,登记号:2021SR0505286.2021年
5)基于小波变换与全变差正则化的信号去噪系统V1.0,计算机软件著作权登记证书,登记号:2020SR0247575.2020年
荣誉奖励:
1)2022年教育厅优秀科技论文一等奖一篇
2)2022年BEVITOR伟德APP官网课程思政教学设计案例大赛二等奖
3)2022年BEVITOR伟德APP官网优秀共产党员
4)2022年BEVITOR伟德APP官网教师教学技能竞赛二等奖
5)2022年河南省第二十六届教育教学信息化交流活动三等奖
6)2021年指导大学生创新创业项目,结项为优秀
7)2019-2021年度BEVITOR伟德APP官网教学优秀奖
8)2019-2020学年BEVITOR伟德APP官网优秀实习指导教师
9)指导全国大学生数学建模竞赛获国家级二等奖一项、省级一等奖四项,省级二、三等奖多项
教学类项目:
1)2023年河南省研究生教育改革与质量提升工程项目(河南省专业学位研究生精品教学案例项目),主持
2)2022年BEVITOR伟德APP官网研究生培养创新与质量提升行动计划项目:专业学位研究生教学案例库,项目号:SYLAL2022016,主持
3)2022年BEVITOR伟德APP官网研究生教育教学改革研究与实践项目,参与
4)2021年度河南省高等教育教学改革研究与实践项目,参与
5)2020年BEVITOR伟德APP官网线上线下混合式本科课程项目,参与