依托南京医科大学国际课程平台，南京医科大学生物医学工程与信息学院特邀法国雷恩大学雷吉娜·勒布坎-让娜（Régine LE BOUQUIN JEANNES）教授开设的《滤波技术》课程将于2026年7月11日正式开启！
Relying on the international course platform of Nanjing Medical University, the College of Biomedical Engineering and Informatics of Nanjing Medical University invites Professor Régine LE BOUQUIN JEANNES from the University of Rennes, France, to teach the course "Filtering Techniques", which will start on July 11th, 2026!
课程描述 Description of Course
本课程主要针对生物医学工程、智能医学工程、生物与医药等相关专业本科生研究生，欢迎相关专业教师、科研人员、医学工程管理人员等参与旁听。整个课程为期5天，课程将从滤波技术基础理论入手，逐步深入核心滤波原理与进阶技术，配套习题研讨与实操实训环节。首日完成课程导论与随机信号基础理论概述，后续三天开展线性滤波、维纳滤波、自适应滤波等核心内容教学与习题研讨，最后一天集中完成基于Matlab实操实训，实现理论与实践的深度融合。总学时为20学时，学习完成者可获得2学分。
This course is primarily designed for undergraduate and graduate students majoring in Biomedical Engineering, Intelligent Medical Engineering, Biology and Medicine, and other related programs. Faculty members, researchers, and medical engineering management professionals from relevant fields are also welcome to audit the course.The 5-day program begins with the fundamental theories of filtering techniques, and progressively delves into core filtering principles and advanced technologies, complemented by dedicated exercise discussion sessions and hands-on practical training modules.On the first day, the course will cover the course introduction and an overview of the basic theories of stochastic signals. Over the following three days, instruction will be delivered on core topics including linear filtering, Wiener filtering, and adaptive filtering, paired with in-depth exercise discussions. The final day is exclusively dedicated to Matlab-based hands-on practical training, to achieve an in-depth integration of theory and practice.The course has a total of 20 class hours, and participants who complete the full program will be granted 2 academic credits.
教授简介 Professor introduction
雷吉娜·勒布坎-让娜（Régine LE BOUQUIN JEANNES），1991年获法国雷恩大学信号处理与电信工程博士学位，现任法国雷恩大学全职教授，雷恩高等工程师学院（ESIR）原生物医学工程系主任，任职于法国国家健康与医学研究院UMR 1099联合研究中心LTSI（信号与图像处理实验室）。同时在南京医科大学、东南大学、深圳技术大学等高校开展合作教学与科研工作，拥有三十余年高校教学经验，自2009年起连续多年为东南大学国际硕士项目开展专业课程授课，年均授课时长约40学时，具备丰富的国际化教学经验。
Régine LE BOUQUIN JEANNES received her PhD in Signal Processing and Telecommunications Engineering from the University of Rennes, France, in 1991. She is currently a Full Professor at the University of Rennes, France, and the Former Head of the Department of Biomedical Engineering at the École Supérieure d'Ingénieurs de Rennes (ESIR). She is affiliated with the Laboratory of Signal and Image Processing (LTSI), UMR 1099, a joint research unit of the French National Institute of Health and Medical Research (INSERM) and the University of Rennes. She also conducts collaborative teaching and research activities at multiple Chinese higher education institutions, including Nanjing Medical University, Southeast University, and Shenzhen Technology University. With over 30 years of teaching experience in higher education, she has been delivering specialized courses for international master’s programs at Southeast University on a continuous basis since 2009, with an average annual teaching load of approximately 40 contact hours, and has accumulated extensive international teaching expertise.
雷吉娜·勒布坎-让娜教授主要从事信号处理、语音增强、神经生理信号（EEG/AEP）分析与表征、脑连接、癫痫、多通道信号处理、远程健康监测、居家健康照护、跌倒检测与日常生活活动分类等领域的研究。累计主持二十余项法国国家级、欧盟及国际合作科研项目，包括数字健康领域ReDHI项目（经费280万欧元）、法国国家科研署ANR ACCORDS项目等；累计发表国内外期刊论文90篇、国际国内会议论文171篇，受邀会议报告6场，拥有2项专利、1项公开数据集、5项软件著作权，累计指导31篇博士学位论文。先后担任法国高等教育与研究评估署（HCERES）评审专家、法国国家大学委员会（信号处理分会）成员、《生物医学工程创新与研究》（IRBM）期刊编委会成员，同时是IEEE、EURASIP等国际权威学术组织会员，以及数十本国际顶级期刊审稿人。
Prof. Régine LE BOUQUIN JEANNES’s primary research areas include signal processing, speech enhancement, analysis and characterization of neurophysiological signals (EEG/AEP), brain connectivity, epilepsy, multichannel signal processing, remote health monitoring, in-home health care, fall detection, and classification of Activities of Daily Living (ADLs). She has served as the Principal Investigator (PI) for more than 20 French national, European Union, and international collaborative research projects, including the ReDHI Project in the digital health field (with a total budget of 2.8 million euros) and the ACCORDS Project funded by the French National Research Agency (ANR).To date, she has published 90 peer-reviewed journal papers and 171 peer-reviewed conference proceedings papers at home and abroad, delivered 6 invited conference presentations, and holds 2 patents, 1 publicly available dataset, and 5 software copyrights. She has supervised 31 PhD dissertations through to completion. She has served as an expert reviewer for the French High Council for Evaluation of Research and Higher Education (HCERES), a member of the French National Council of Universities (CNU) Section for Signal Processing, and a member of the Editorial Board of Innovation and Research in Biomedical Engineering (IRBM). She is also a member of leading international academic organizations including the Institute of Electrical and Electronics Engineers (IEEE) and the European Association for Signal Processing (EURASIP), and acts as a reviewer for dozens of top-tier international journals.
讲课内容 Course Outline and Assignment
1. 课程基础理论：系统讲解滤波技术的发展与应用场景，回顾概率论核心知识点，深入阐释随机过程的核心概念，包括随机信号、平稳性与遍历性，为滤波技术学习搭建完整的理论基础框架。
1. Fundamental Course TheoriesThis module systematically explains the development history and application scenarios of filtering techniques, reviews core knowledge points of probability theory, and provides in-depth interpretation of core concepts of stochastic processes, including stochastic signals, stationarity, and ergodicity, to build a complete theoretical framework for the learning of filtering techniques.
2. 线性滤波与随机模型内容：讲解线性滤波的核心原理，结合含噪双正弦信号开展初步应用教学，深入阐释随机模型的构建方法，包括ARMA、MA和AR模型在信号估计与预测中的应用，实现理论与基础应用的结合。
2. Linear Filtering and Stochastic ModelsThis module explains the core principles of linear filtering, conducts preliminary application-oriented teaching with noisy dual sinusoidal signals, and provides in-depth elaboration of the construction methods of stochastic models, including the application of AutoRegressive Moving Average (ARMA), Moving Average (MA), and AutoRegressive (AR) models in signal estimation and prediction, to realize the integration of theory and basic application.
3. 最优化滤波核心技术：系统讲解连续域与离散域维纳滤波的原理与实现方法，配套线性预测相关内容教学，通过专项习题课深化学生对AR模型、最优滤波核心知识点的理解与应用能力，夯实最优滤波技术基础。
3. Core Optimal Filtering TechniquesThis module systematically explains the principles and implementation methods of Wiener filtering in both continuous-time and discrete-time domains, complements the teaching with content related to linear prediction, and deepens students' understanding and application ability of core knowledge points of AR models and optimal filtering through specialized exercise sessions, to consolidate the foundation of optimal filtering techniques.
4. 自适应滤波技术：深入讲解自适应滤波的核心原理与最小均方（LMS）算法，拓展滤波技术在生物医学信号处理、语音降噪等领域的进阶应用，配套完整的实操教学环节。
4. Adaptive Filtering TechniquesThis module provides in-depth explanation of the core principles of adaptive filtering and the Least Mean Square (LMS) algorithm, expands the advanced application of filtering techniques in fields including biomedical signal processing and speech noise reduction, and is complemented with complete hands-on teaching modules.
5. 实操实训与课程落地：通过基于Matlab软件的实操课程，指导学生完成基于自适应滤波的降噪处理全流程开发，实现课程理论知识的工程化落地，完成课程实践教学目标。
5. Practical Training and Course ImplementationThrough Matlab-based hands-on courses, this module guides students to complete the full-process development of noise reduction processing based on adaptive filtering, realizes the engineering implementation of the theoretical knowledge covered in the course, and fulfills the practical teaching objectives of the course.
报名与安排 Registration and Arrangement
如果您想要报名可于2026年7月9日前通过学院指定官方渠道完成报名，本次课程学习免费，主要为生物医学工程、智能医学工程、生物与医药等相关专业本科生研究生开设，报满30人为止。如有其他问题可联系课程助理咨询相关信息。
If you wish to register for the course, please complete your registration via the official channels designated by the college on or before July 9, 2026. This course is offered free of charge, and is primarily designed for undergraduate and graduate students majoring in Biomedical Engineering, Intelligent Medical Engineering, Biology and Medicine, and other related programs. Enrollment is capped at 30 participants, and registration will close once the maximum capacity is reached. Should you have any other questions, please contact the course assistant for further information.
联络人 Contacts
协调专员：向文涛
课程助理：陈智琪（Tel/Wechat: 18351956592）
授课地点：南京医科大学生物医学工程与信息学院指定授课场地
Coordinator: Wentao Xiang
Assistant: Zhiqi Chen（Tel/Wechat: 18351956592）
Location: Designated teaching venue of College of Biomedical Engineering and Informatics, Nanjing Medical University
发布审核：刘继永、高珍秀
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