Onufriienko D., Taranenko Y.
Filtering and compression of signals by the method of discrete wavelet transformation into one-dimensional series

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. © 2023, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: database, discrete wavelet analysis, identification measurements, linear and non-linear modulation, one-dimensional series, series proximity measures, Wavelet analysis, Discrete wavelets analysis, Identification measurement, Linear and non-linear modulation, Linear modulations, Nested arrays, Non linear, One-dimensional, One-dimensional series, Proximity measure, Series proximity measure, Wavelet decomposition

Cite:
Onufriienko D., Taranenko Y. (2023). Filtering and compression of signals by the method of discrete wavelet transformation into one-dimensional series. Cybernetics and Systems Analysis, 59 (2), 173–182. doi: https://doi.org/10.1007/s10559-023-00567-1 http://jnas.nbuv.gov.ua/article/UJRN-0001392167 [In Ukrainian].