Digital Signal Extraction by Means of Nonlinear Stochastic Filtration




stochastic resonance, signal-to-noise ratio, filter, nonlinear stochastic filter, matched filter, digital signal, dispersion, white Gaussian noise, nonlinear distortions


The results of noise immunity analysis for digital communication systems using methods of nonlinear filtering are given. Nonlinear filtration is based on stochastic resonance effect. The stochastic resonance is given to a phenomenon that is manifest in nonlinear systems where by generally feeble input information (such as a weak signal) can be amplified and optimized by the assistance of noise. The stochastic resonance has been observed in a large variety of systems, including bistable ring lasers, semiconductor devices, chemical reactions, and mechanoreceptor cells in the tail fan of a crayfish. Numeral simulation of response at affecting input of the system on additive mixture of harmonic signal and white Gaussian noise are given. Amplitude spectrum of this output signal has been investigated. Results of the output signal-to-noise ratio calculation of the stochastic filter for the additive sum of a harmonic signal and white Gaussian noise for different values of the input noise dispersion are given. It is shown that the output signal-to-noise ratio of the system will peak at a certain value of noise intensity under a action of the input signal and noise. It is shown that the stochastic resonance effect provides separation of a digital signal from the white Gaussian noise. The comparative analysis of noise immunity of the matched filter and nonlinear stochastic filter for input square pulses are given. The effects of signal distortions in nonlinear processing with a stochastic filter are considered. Calculations of the coefficient of nonlinear distortions of a rectangular pulse are performed. It is shown that nonlinear distortions lead to a decrease in the signal-to-noise ratio at the output of the filter.

Author Biographies

O. I. Kharchenko, Kharkiv National University of Radioelectronics

Kharchenko O. I., Cand. of Sci (Techn)

V. M. Kartashov, Kharkiv National University of Radioelectronics

Kartashov V. M., Doc. of Sci (Techn.), Prof.


Sklar B. (2001) Digital communication. Fundamental and Application, Prentice Hall, 1104 p.

Hadden A. D. (1995) Personal Communications Networks: Practical Implementation, Artech House, 294 p.

Irvine J. R. and Harle D. (2002) Data Communication and Networks: An Engineering Approach, John Wiley & Sons, 288 p.

Anishchenko V., Boev Y., Semenova N. and Strelkova G. (2015) Local and global approaches to the problem of Poincaré recurrences. Applications in nonlinear dynamics. Physics Reports, Vol. 587, pp. 1-39. DOI: 10.1016/j.physrep.2015.05.004

Barbini L., Cole M.O.T., Hillis A.J. and du Bois J.L. (2015) Weak signal detection based on two dimensional stochastic resonance. 2015 23rd European Signal Processing Conference (EUSIPCO). DOI: 10.1109/eusipco.2015.7362764

Levin B.R. (1969) Teoreticheskie osnovy statisticheskoi radiotekhniki [Basis of stochastic radioengineering], Moskow, Sov. Radio Publ., p. 752.

Kharchenko O. (2015) Analysis on the Basis of Volterra Series Signal–To–Noise Ratio of Nonlinear Device in the Conditions of the Stochastic Resonance Effect. Journal of Electrical and Electronic Engineering, Vol. 3, Iss. 3, pp. 25. DOI: 10.11648/j.jeee.20150303.11

Spagnolini U. (2017) Statistical Signal Processing in Engineering, John Wiley & Sons, 608 p. DOI: 10.1002/9781119294016

Voloshchuk Yu. I. (2005) Syhnaly ta protsesy u radiotekhnitsi. Tom 3 [Signals and processes in radioengineering. Volume 3], Kharkiv: CMIT, 528,p.

Kharchenko O.I. and Gorban A.M. (2017) Non-linear filtering of pulse signals in case of high intensity noise. >Problems of Atomic Science and Technology, No. 6(112), pp. 113-116.

He Q. and Wang J. (2012) Effects of multiscale noise tuning on stochastic resonance for weak signal detection. Digital Signal Processing, Vol. 22, Iss. 4, pp. 614-621. DOI: 10.1016/j.dsp.2012.02.008

Williams D. (2017) Understanding, Calculating, and Measuring Total Harmonic Distortion (THD). Available at:

Mazor Yu. L. eds., Machusskiy E. A. and Pravda V.I. (2002) Radiotekhnika: Ensiklopedia [Radio engineering: Encyclopedia], Moskow, Dodeka-XXI, 944 p.




How to Cite

Kharchenko, O. I. and Kartashov, V. M. (2018) “Digital Signal Extraction by Means of Nonlinear Stochastic Filtration”, Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, 0(73), pp. 50-54. doi: 10.20535/RADAP.2018.73.50-54.



Computing methods in radio electronics