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The Wavelet Transform (WT) has been developed two decades ago, and has since then been put to use in an increasingly wide array of applications. The WT provides a time-scale analysis of a signal. Compared to the widely-popular Fourier Transform (FT), originally developed two hundred years ago, the WT provides the time-evolution of the signal at different scales. The Discrete Wavelet Transform (DWT) is a computationally efficient implementation of the WT, in which the time-scale analysis is performed on a dyadic scale. The DWT is very suitable for knock detection systems, since it can provide the history of the knock signal at discrete scales within a crank angle window. It allows for the extraction of a multitude of features from the time-scale plane. Moreover, the DWT is suitable for real-time knock detection implementations on engine control units.