MODELING OF THE VECTOR OF SAMPLES OF STATIONARY RANDOM PROCESSES IN DIGITAL SIGNAL PROCESSING SYSTEMS
A. G. Vostretsov1,2, S. G. Filatova1,3, D. I. Volkhin1
1Novosibirsk State Technical University, Novosibirsk, Russia
2N. A. Chinakal Institute of Mining Engineering, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
3Federal Institute of Industrial Property, Moscow, Russia
Keywords: digital modeling, random sequence, power spectral density, stationary random process
Abstract
A method of modeling random sequences composed of digital samples of stationary random processes with a given power spectral density (PSD) in systems with digital signal processing (DSP) is proposed. The method takes into account the limitation of the signal spectrum by the input devices of DSP systems and the peculiarities of the transfer function representation using the fast Fourier transform. Digital white noise with the Gaussian or uniform distribution is taken as an initial process for modeling. It is shown that the PSD estimation of the sequences obtained as a result of modeling is unbiased, and its mean value coincides with the samples of the initial PSD. An expression for calculating the RMS error of the estimation is derived.
|
