Time-frequency analysis - G

Methods such as wavelets and M-stationary process have been developed to analyze the time-frequency properties of a process where frequency changes with time. In certain circumstances, when the frequencies of a process change systematically either monotonically increasing or monotonically decreasing across time, another approach is to apply an appropriate Box-Cox transformation to the time axis for the given signal in order to obtain a new stationary data set. This new data set can be analyzed by standard methods. Processes which are transformed to a stationary process after Box-Cox transformation on the time scale are called G()-stationary processes, where is the corresponding parameter of the Box-Cox transformation. The method is illustrated with analysis of both simulated and real data. Finally, it is shown that such processes can be transformed to stationarity by sampling properly. 1 

• Type: Journal
• Year: 2006
• Where: CSDA
• Authors: Huiping Jiang, Henry L. Gray, Wayne A. Woodward
• Keywords: Appropriate Box-cox Transformation, Box-Cox Transformation, CSDA 2006, Time-frequency Properties