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Activity Number:
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54
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Type:
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Topic Contributed
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Date/Time:
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Sunday, July 29, 2007 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #309842 |
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Title:
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Time-Frequency Analysis: G(lambda)-stationary Processes
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Author(s):
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Huiping Jiang*+ and Henry L. Gray and Wayne Woodward
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Companies:
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Columbia University and Southern Methodist University and Southern Methodist University
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Address:
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1051 Riverside Drive, New York, NY, 10032,
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Keywords:
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time-frequency ; M-stationary process
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Abstract:
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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(lambda)-stationary processes, where lambda is the corresponding parameter of the Box-Cox transformation.
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