首页> 外文期刊>International Journal of Electrical Engineering Education >A MATLAB-based biomedical signal de-noising applied to digital signal processing course for third-year students
【24h】

A MATLAB-based biomedical signal de-noising applied to digital signal processing course for third-year students

机译:基于MATLAB的生物医学信号降噪技术应用于三年级学生的数字信号处理课程

获取原文
获取原文并翻译 | 示例
       

摘要

Signal de-noising is one of the major topics of engineering application covered in an undergraduate-level digital signal processing course. Generally speaking, it involves a number of tedious concepts that have intrinsic physical meaning, which is difficult for students to understand . In this paper, an educational method using diaphragmatic electromyographic (EMGdi) as the de-noising object, which runs on the MATLAB software, has been developed for the convenience of learning and understanding for three-years students in digital signal processing course. This method transforms the analog filter to a digital filter by applying bilinear transformation equations, which allows the students explore the various characteristics of digital filter, such as low pass filter, high pass filter, band pass filter and band stop filter. That means Laplace equation transformed by inductance, capacitance and resistance will be replaced by the z equation, which is used for deriving sequence of difference equations. In the case studies, the clinical EMGdi is used to show the features of the developed method. Furthermore, classroom experience in the Nanfang College of Sun Yat-sen University has shown that the developed method helps in consolidating a better understanding of signal de-noising processing in digital signal processing course.
机译:信号降噪是本科级别的数字信号处理课程所涵盖的工程应用的主要主题之一。一般来说,它涉及许多具有内在物理意义的繁琐概念,这使学生难以理解。本文开发了一种在MATLAB软件上运行的以diaphragm肌肌电(EMGdi)为降噪对象的教学方法,以方便三年级学生学习和理解数字信号处理课程。这种方法通过应用双线性变换方程将模拟滤波器转换为数字滤波器,这使学生可以探索数字滤波器的各种特性,例如低通滤波器,高通滤波器,带通滤波器和带阻滤波器。这意味着由电感,电容和电阻转换的拉普拉斯方程将由z方程代替,该z方程用于推导差分方程的序列。在案例研究中,临床EMGdi用于显示开发方法的功能。此外,中山大学南方学院的课堂经验表明,所开发的方法有助于巩固对数字信号处理课程中信号降噪处理的更好理解。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号