San Diego State University (SDSU) Prof. Sam Shen and his students are visiting ITP at Beijing for academic exchanges. Their visit also tended to exploit field for further cooperation in effectively and plausibly reconstructing paleo-climate from various proxies. Invited by ITP Prof. YAO Tandong, they will present their latest mathmatical approach in time-series analysis for climate changes.

Welcome to attend the seminar! Discussion with them will open a new window for you in viewing your data mathematically.

Report: An Introduction to the Hilbert-Huang Transform and its Applications to Time-Series Analysis

Presenter: David New, a master’s candidate in the Department of Mathematics and Statistics, SDSU. He has been actively engaged in the exploitation of Hilber-Huang transform and its application in time-series analysis in climate change verification. He is also ready to demonstrate the usage and share with you his code for the application.

Venue: meeting room on the second floor of ITP office building

Time: 8.00-9.30 am, Thursday, June 16, 2011

Abstract: .

The Hilbert-Huang transform (HHT) is a recently developed method for analyzing frequencies present in time-series. The standard method for analyzing time-series has for many years been Fourier analysis, which suffers from several drawbacks. The Fourier transform decomposes a time-series into a sum of waves with constant amplitudes and frequencies which do not usually have a physical interpretation. The advantage of HHT is that it decomposes a time-series into a sum of waves with amplitudes and frequencies that can change over time and which often do have physical meaning. Also, the Fourier transform is not well suited for analyzing time-series that are nonstationary or nonlinear but by allowing frequencies and amplitudes to change over time, HHT overcomes this problem.