Paper
2 May 2017 The synthesis of the correlation function of pseudorandom binary numbers at the output shift register
G. G. Galustov, V. V. Voronin
Author Affiliations +
Abstract
The sequence generator generates a sequence of pseudorandom binary numbers using a linear-feedback shift register (LFSR). This block implements LFSR using a simple shift register generator (SSRG, or Fibonacci) configuration. In this article we introduce the concept of probabilistic binary element provides requirements, which ensure compliance with the criterion of "uniformity" in the implementation of the basic physical generators uniformly distributed random number sequences. Based on these studies, we obtained an analytic relation between the parameters of the binary sequence and parameters of a numerical sequence with the shift register output. The received analytical dependencies can help in evaluating the statistical characteristics of the processes in solving problems of statistical modeling. It is supposed that the formation of the binary sequence output from the binary probabilistic element is produced using a physical noise process. It is shown that the observed errors in statistical modeling using pseudo-random numbers do not occur if the model examines linear systems with constant parameters, but in case models of nonlinear systems, higher order moments can have a Gaussian distribution.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
G. G. Galustov and V. V. Voronin "The synthesis of the correlation function of pseudorandom binary numbers at the output shift register", Proc. SPIE 10200, Signal Processing, Sensor/Information Fusion, and Target Recognition XXVI, 102001G (2 May 2017); https://doi.org/10.1117/12.2263590
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Binary data

Barium

Correlation function

Statistical analysis

Systems modeling

Complex systems

Statistical modeling

Back to Top