Application of wavelet analysis in time series analysis in the field of coastal engineering
A study of the applicability of wavelet analysis for time series in coastal engineering. This signal processing technique already has a lot of applications in many engineering fields. There are two main transforms: the continuous wavelet transform and the discrete wavelet transform. The continuous one is used much as a mean to give detailed information of the energy distribution of a signal in the time-frequency domain. The application of this transform, in the context of statistical significance is the main subject of my first research question. The discrete wavelet transform gives a much more redundant representation of a signal, which is much used in compression. Furthermore, the noise suppressing characteristics will be compared to current filtering methods, such as Fourier domain filtering. The largest advantage of wavelet filtering is the ability to filter high frequency noise, without smoothing discontinuities. My last research question has to objective to describe the added value of wavelet analysis, in order to persuade engineers from the field of the high applicability of this method.
Research question: How can wavelet analysis improve time series analysis in the field of coastal engineering?
Subquestions:
- How to recognize and identify different signal components in coastal engineering time series?
- How to remove or reduce different types of noise efficiently in coastal engineering time series?
- What is the added value of wavelet analysis over current time series analysis methods in coastal engineering?
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