The use of wavelet transformations in chemometrics started in the early 1990-ies have proven to be very useful for noise suppression, data shortening, and quantitative analysis based on linear models [1, 2]. In this work, wavelet method was used for increase of resolution and sensitivity that are the most important characteristics of analytical instruments. Wavelet processing was performed by utilization of synthesized or modified wavelets oriented on the treatment of signal for certain class of instruments or adapted for specific type of instrument. Synthesis is based on information a priori on the apparatus function, noise correlation function, and specifications for apparatus on the stage of primary treatment [3, 4, 5]. Presented approach allows to broaden wavelet processing on the calculation of noise estimations for not only signal but also for linear transformation of this signal. Demonstrated fast algorithms can be realized in real time by compact computing devices. Application of the method for analytical instruments allows to increase sensitivity three or four times and ,simultaneously, resolution for rises up to the separation of completely overlapping peaks.

References:
1. Jetter K., Depezynski U., Molt K., Niemöller A. Principles and applications of wavelet transformation to chemometrics// Analytica Chimica Acta. 2000. V.420. P.169–180.
2. Rodionova O.Ye. , Pomerantcev A.L., Chemometrics: achievements and prospects// Uspechi chimii (Russia). 2006. V.75 №4. P. 302–317.
3. Novikov. L.V. Wavelet - Based Deconvolution// Instruments and Experimental Techniques. 2007, vol.50, N1.
4. Novikov. L.V. Orthonormal Quasi-Wavelets for Signal Processing
//Izv, Vuzov. Priborostroenie (Russia). 2007, V.50, №1. P. 3–10.
5. Novikov. L.V. Modified Wavelets and Their applications// Journal of Communication Technology and Electronics. 2006. V.51. №11. P. 1337–1346.