**报告题目：**Ways to Extract Time-Varying Frequencies from Signals
**报告时间：**2019年5月24日(周五)下午16:00-17:00
**报告地点：**数理楼3503
**报**** ****告**** ****人：**朱洪梅教授 （加拿大约克大学）
**摘要：**In many signal processing applications, it is often important to extract frequency information from a signal, particularly if the signal evolves in time. Traditional data analysis methods, such as the Fourier transform, represent a signal in frequency domain and are not effective when dealing with non-stationary signals. Time-frequency analysis has been developed to overcome the limitations of the traditional techniques by representing a signal as a joint function of both time and frequency. Hence time-varying frequency information can be revealed. However, due to the Heisenberg's uncertainty principle, the resolution of a joint time-frequency representation may not be accurate enough to separate multiple frequency components well; this becomes more challenging when noise is present. In this talk, we overview the development of extract time-varying frequency information from a non-stationary signal and proposed a method that is accurate and automatic. Examples and applications will be discussed.
**报告人简介：**Dr. Hongmei Zhu is an Associate Professor at the Department of Mathematics and Statistics, York University. She holds a PhD in Applied Mathematics at the University of Waterloo in 2000. Upon graduation, she was awarded as a MS Society of Canada postdoctoral fellowship at the Seaman MR Centre at Foothills Hospital, University of Calgary between 2001 and 2004. Hongmei’s research interests are in the areas of time-frequency analysis, data science, numerical computations and their applications in real-world problems arisen from bio-medicine and other industries.
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