Wavelet Use for Noise Rejection and Signal Modelling
Aleš Procházka, Martina Mudrová, Martin Štorek · Applied and numerical harmonic analysis · 1998
Wavelet functions form an essential tool of modern signal analysis and modelling in various engineering, biomedical and environmental systems. The paper is devoted to selected aspects of construction of wavelet functions and their properties enabling their use for time-scale signal analysis and noise rejection. The main part of the paper presents the basic principles of signal decomposition in connection with fundamental signal components detection and approximation. The methods are verified for simulated signals at first and then used for real signal analysis representing air pollution inside a given region of North Bohemia covered by several measuring stations. The following part of the chapter is devoted to comparison of linear and non-linear signal modelling and prediction for original and de-noised signals. The paper emphasizes the algorithmic approach to methods of signal analysis and prediction and it presents the use of wavelet functions both for signal analysis and modelling. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.