Abstract
Numerical methods for expanding the field of applicability of chromatography-mass spectrometry in the case of poorly separated signals are considered. We found that the existence of additive noise in the initial mixed mass spectrum gives rise to the noise component of the weight coefficients of its components with an undetermined probability distribution law. The power of the generated noise is higher than the power of the additive noise of the output signal. It is shown that the condition of orthogonality of the components of the mixed mass spectrum makes it possible to determine their weight coefficients with a relative error of less than 4% when the ratio of the power of additive noise to the power of the useful signal is not more than three times. The main result of the work, which is new compared to the one published earlier, is that for real mass spectra it was shown that decomposition of a linear combination of orthogonal functions by the optimal linear associative memory (OLAM) method gives a satisfactory result even if the noise level is three times higher than the useful signal level. The area of satisfactory application of OLAM for the decomposition of non-orthogonal functions, on the contrary, is limited by the condition that the signal level exceeds the noise level by about 2.5 times.
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Olszewski, S. et al. (2020). Expansion of the Capabilities of Chromatography-Mass Spectrometry Due to the Numerical Decomposition of the Signal with the Mutual Superposition of Mass Spectra. In: Babichev, S., Peleshko, D., Vynokurova, O. (eds) Data Stream Mining & Processing. DSMP 2020. Communications in Computer and Information Science, vol 1158. Springer, Cham. https://doi.org/10.1007/978-3-030-61656-4_14
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