Solving the problem of identifying special signals under a priori uncertainty of their sources is extremely important, for example, when detecting locators working on moving objects. The method provides the filtering signals from powerful noises (up to – 12 dB) and determining the signal shape. The signal identification, filtering, and compression based on comparing the proximity of one-dimensional series of wavelet coefficients are considered. The article proposes the direct transformation of nested arrays of the approximation and detail coefficients into a one-dimensional series with a preliminary determination of the structure of the nested arrays for further reconstruction of the one-dimensional series into an identifiable measurement signal. The robustness of the proposed algorithm to local changes in the shape of the test signal according to the identification requirements is verified.
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Translated from Kibernetyka ta Systemnyi Analiz, No. 2, March–April, 2023, pp. 173–181.
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Onufriienko, D., Taranenko, Y. Filtering and Compression of Signals by the Method of Discrete Wavelet Decomposition into One-Dimensional Series. Cybern Syst Anal 59, 331–338 (2023). https://doi.org/10.1007/s10559-023-00567-1
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DOI: https://doi.org/10.1007/s10559-023-00567-1