DISCRETE WAVELET TRANSFORMS
4.1 INTRODUCTION
In the second chapter we introduced linear filters and presented examples of commonly used filters in economics and finance. Our toolbox of available filters was expanded in Chapter 3 with the Wiener and Kalman filter. Here we introduce the discrete wavelet transform (DWT). The DWT has several appealing qualities that make it a useful method for time series, exhibiting features that vary in both time and frequency. Although developed originally with geophysical applications in mind (Goupilllaud et al., 1984), the DWT and its variants have found a home in a wide variety of disciplines—geology, atmospheric science, turbulence, and applied mathematics, to name a few. The engineering community quickly ...
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