Solutions to non-traditional problems of signal recognition are considered. Special treatment is given to the case when defined in the probabilistic sense signals to recognize are mixed with unknown signals. Methods for selection and recognition of a defined random signal are proposed for the cases when signal’s description is done by various probabilistic models. Real-life peculiarities of application of methods for selection and recognition of a defined random signal in the field of radiolocation, automated radiomonitoring, medical diagnostics and speaker identification are given.
- K.Fukunaga, Introduction to statistical pattern recognition. San Diego, USA: Academic Press, 1990.
- V. A.Omelchenko, Foundations the spectral theory of signal recognition. Kharkiv, Ukraine: Vyshcha Shkola, 1983. (Russian)
- A.Webb, Statistical pattern recognition. New York, USA: Wiley, 2002.
- V. M.Bezruk and G. V. Pevtsov, Theoretical foundations of signal recognition systems design for automated radio monitoring. Kharkiv, Ukraine: Kollegium, 2007. (Russian)
- V. M.Bezruk and V. A.Omelchenko, “Recognition of radar objects by range portraits in the framework of orthogonal series expansions” in Proc. The First International Workshop NOISE RADAR TECHNOLOGY, рp. 245‑250, Yalta, Ukraine, 2002. (Russian)
- V. M.Bezruk, “Autoregressive methods of signal recognition”, Telecommunications and Radio Engineering, vol. 56(12-14), pp. 12‑18, 2003.
- V. M.Bezruk and O. G.Lebedev, “A method for radiolocation recognition of object types at wideband probing based on vector autoregressive model”, Applied radio electronics, vol. 4, no 3, pp. 336‑339, 2005. (Russian)
- V. M. Bezruk, Y. N. Belov, O. A. Voytovich, K. A. Netrebenko, V. A. Tikhonov, G. A. Rudnev, G. I. Khlopov, and S. I. Khomenko, “Radiolocation recognition of meteorological objects based on autoregressive model of a reflected signal”, Applied radio electronics, no 2, pp. 35 ‑ 40, 2010. (Russian)
- V. M. Bezruk, N. P.Kovalenko, and V. A.Lysenko, “A method for sleep stage recognition with respect to an encephalogram and based on the autoregressive model”, Intelligence bionics, no 1, pp. 45‑48, 2005. (Russian)
- A. V.Fedorov and A. V.Omelchenko, “Synthesis and research into algorithms for speaker identification by characteristics of linear prediction residuals”, Radio electronics and informatics, no 4, pp. 71‑75, 2006. (Russian)