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An Alternative Method for Generating Almost Infinite Sequence of Gaussian Variables

Authors: Nyah C. Temaneh, F. A. Phiri, E. Ruhunga


Most of the well known methods for generating Gaussian variables require at least one standard uniform distributed value, for each Gaussian variable generated. The length of the random number generator therefore, limits the number of independent Gaussian distributed variables that can be generated meanwhile the statistical solution of complex systems requires a large number of random numbers for their statistical analysis. We propose an alternative simple method of generating almost infinite number of Gaussian distributed variables using a limited number of standard uniform distributed random numbers.

Keywords: Statistical Analysis, Random Numbers, Gaussian variable, simulation ofCommunication Network

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[1] James E. Gentle. Random Number Generation and Monte Carlo Methods, Series: Statistics and Computing. 2nd ed. 2003. Corr. 2nd printing, 2003, XV, 300 p., Hardcover. ISBN: 978-0-387-00178-4
[2] Nyah. C. Temaneh, "Monte-Carlo Technique Estimation of a Probability of Intermodulation Interference in a Cellular Wireless Communication Network", Proceedings 2010 IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, Irkutsk, Russia 2010, pp. 329 - 334.
[3] Nyah. C. Temaneh, K. E. Vinogradov, A. N. Krenev, "Monte-Carlo based estimation of probabilistic characteristics of signal to noise ratio with GSM 900 cellular communication network as case study (in Russian)", in Proceedings of IX international scientific - technical conference on Radiolocation, Navigation and Communication, Voronesh (Russia), vol. 2, 2005, pp. 1182 - 1188.
[4] Nyah. C. Temaneh, "Estimation of a probability of interference in a cellular communication network using the Monte Carlo Technique." Proceedings of the Southern African Telecommunications and Networks Conference, SATNAC 2009, Swaziland, September 2009.
[5] ERC Report 68,"Monte-Carlo Simulation Methodology for the use in sharing and compatibility studies between different radio services or systems" Naples, February 2000
[6] D. H. Lehmer. Mathematical methods in large-scale computing units. In Proc. 2nd Sympos. On Large Scale Digital Calculating Machinery, Cambridge, MA, 1949, PP. 141-146, Cambridge, MA, 1951. Harvard University Press.
[7] Gurskiy E. I., Probability theory with elements of mathematical statistics. Moscow, 1971.