刘秀玲 - 河北大学 - 电子信息工程学院

个人简介

2002年毕业于天津大学电力系统及其自动化专业获硕士学位，2010年毕业于河北大学光学工程专业获得博士学位。

研究领域

主要从事自动化领域的智能建模方法与控制研究，近年来主要围绕复杂系统的建模与智能分析及其在心血管疾病诊疗中的应用开展工作。将最新的深神经网络控制方法引入到心血管系统的建模过程中，实现了人体模型中心电信号和医学影像的特征提取以及心梗等重大疾病的复杂网络模型建立和智能分析。

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

1、C.G. Lou, S. Wang, T. Liang, C.Y. Pang, L. Huang, M.T. Run and X.L Liu*. “A graphene-based flexible pressure sensor with applications to plantar pressure measurement and gait analysis”. Materials, 2017, 10(9):1-11. (SCI, IF=2.654, 二区). 2、J.L. Yang, Y. Bai, F. Lin, M. Liu, Z.G. Hou, X.L. Liu*. “A novel electrocardiogram arrhythmia classification method based on stacked sparse auto-encoders and softmax regression”. International Journal of Machine Learning & Cybernetics, 2017(4):1-8. (SCI, IF=1.699) 3、M. Liu, H.Q. Hao, P. Xiong, F. Lin, Z.G. Hou, X.L. Liu*. “Constructing a guided filter by exploiting the butterworth filter for ECG signal enhancement”. Journal of Medical & Biological Engineering, 2017(9):1-13. (SCI, IF=0.989) 4、P. Xiong, H.R. Wang, M. Liu, S.P. Zhou, Z.G. Hou, X.L. Liu*. “ECG signal enhancement based on improved denoising auto-encoder”. Engineering Applications of Artificial Intelligence, 2016, 52(C):194-202. (SCI, IF=2.894, 二区). 5、刘明, 李国军, 郝华青, 侯增广, 刘秀玲*. “基于卷积神经网络的T波形态分类”. 自动化学报, 2016, 42(9):1339-1346. (EI) 6、C.G. Lou, R.K. Li, Z.P. Li, T. Liang, Z.H. Wei, M.T. Run, X.B. Yan and X.L. Liu*. “Flexible graphene electrodes for prolonged dynamic ECG monitoring”. Sensors, 2016, 16(11):1-12. (SCI, IF=2.677, 三区). 7、P. Xiong, H.R. Wang, M. Liu, F. Lin, Z.G. Hou, X.L. Liu*. “ A stacked contractive denoising auto-encoder for ECG signal denoising”. Physiological Measurement, 2016, 37(12):2214-2230. (SCI, IF=2.058). 8、X.L. Liu, H.M. Du, G.L. Wang, S.P. Zhou, H. Zhang. “Automatic diagnosis of premature ventricular contraction based on Lyapunov exponents and LVQ neural network”.Computer Methods & Programs in Biomedicine, 2015, 122(1):47-55. (SCI, IF=2.503, 三区). 9、P. Xiong, H.R. Wang, M. Liu, X.L. Liu*.“Denoising autoencoder for eletrocardiogram signal enhancement”. Journal of Medical Imaging & Health Informatics, 2015, 5(8):1804-1810. (SCI, IF=0.621). 10、J.L. Yang, Y. Bai, G.J. Li, M. Liu, X.L. Liu*. “A novel method of diagnosing premature ventricular contraction based on sparse auto-encoder and softmax regression”. Bio-medical Materials and Engineering, 2015, 26 Suppl 1(s1):S1549. (SCI, IF=0.700).

学术兼职

河北省机器学习学会副理事长