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Lian, S.G., Liu, Z.X., Ren, Z. and Wang, H.L. (2006) Hash Function Based on Chaotic Neural Networks. 2006 IEEE International Symposium on Circuits and Systems, ISCAS 2006, Island of Kos, 21-24 May 2006.
http://dx.doi.org/10.1109/iscas.2006.1692566

has been cited by the following article:

• TITLE: A Novel Triangular Chaotic Map (TCM) with Full Intensive Chaotic Population Based on Logistic Map

  AUTHORS: Mahmoud Maqableh

  KEYWORDS: Chaos, Chaotic Maps, Triangular Chaotic Map, Logistic Map, Lyapunov Exponent

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.8 No.12, December 31, 2015

  ABSTRACT: Chaos theory attempts to explain the result of a system that is sensitive to initial conditions, complex, and shows an unpredictable behaviour. Chaotic systems are sensitive to any change or changes in the initial condition(s) and are unpredictable in the long term. Chaos theory are implementing today in many different fields of studies. In this research, we propose a new one-dimensional Triangular Chaotic Map (TCM) with full intensive chaotic population. TCM chaotic map is a one-way function that prevents the finding of a relationship between the successive output values and increases the randomness of output results. The tests and analysis results of the proposed triangular chaotic map show a great sensitivity to initial conditions, have unpredictability, are uniformly distributed and random-like and have an infinite range of intensive chaotic population with large positive Lyapunov exponent values. Moreover, TCM characteristics are very promising for possible utilization in many different study fields.