Time Series Data Analysis for Civil, Mechanical and Geophysical Applications

3.0 credits · Graduate

Data acquired as time series are increasingly common in age of GPS, smart phones, and wireless data transfer. This course will cover data processing tools and techniques that allow us to efficiently manipulate and better understand the data and the physical world that they sample. Course topics include Fourier transforms, convolution, filtering, data acquisition, noise, linear systems, and AutoRegressive Moving Average (ARMA) models. Topics are covered both from theoretical (continuous, analog signals) and practical (discrete-time digital signals) viewpoints. More advanced topics will emphasize the analysis of transient and non-stationary time series such as earthquake ground motions, structural or environmental response to extreme events, and other signals related to engineering and earth science disciplines.