A Study on System Identification Using Wavelet Transformation

The wavelet transformation, which was developed in order to overcome the defects of traditional Fourier trans- formation, is applied to many fields of study in various ways-for example, de-noising, data compression and mathematic appli- cations such as solving partial differential equations, etc. De-noising is one of the main application areas of the wavelet transformation and has been studied by many researchers. The effect of de-noising depends upon the shrinkage function and the method of choosing the threshold value for the function. The objective of this work is to analyze the results of applying v ar- ious threshold algorithms according to characteristics for signals and noise level. By applying the de-noising to the system identification, we compared the performances of signals which went through the de-noising process with those of signals with- out de-noising.