Applications Related to the Sensors Field

In the last decade, numerous applications of the WT have been proposed for chemical analysis. One of the main goals in analytical chemistry is to extract useful information from recorded data however, data gathered from experiments is contaminated with noise. Band-pass filtering behaviour of WT has been successfully applied to the removal of noise or trends, and smoothing (Alsberg et al. 1997). 

Data compression is another application of WT that has shown remarkable results (Artursson and Holmberg 2002). The mathematical treatment for data compression by WT is similar to that for denoising and smoothing (fetter et al. 2000). Chemical data is treated with WT and transformed to the scale-time domain where its spectral content is reduced by elinunating coefficients belonging to high frequency content. Compression with this teclmique is highly efficient since a one level decomposition and 

Chromatography, infrared spectroscopy, mass spectrometry, nuclear magnetic resonance spectroscopy, ultraviolet-visible spectroscopy and others have also been benefited from the properties of wavelet processing for data compression, noise removal, base-line correction, zero crossing and regression (Leung et al. 1998). 

---