An Information Theoretic Analysis of Random Number Generator based on Cellular Automaton

Abstract

Realization of Randomness had always been a controversial concept with great importance both from theoretical and practical Perspectives. This realization has been revolutionized in the light of recent studies especially in the realms of Chaos Theory, Algorithmic Information Theory and Emergent behavior in complex systems. We briefly discuss different definitions of Randomness and also different methods for generating it. The connection between all these approaches and the notion of Normality as the necessary condition of being unpredictable would be discussed. Then a complex-system-based Random Number Generator would be introduced. We will analyze its paradoxical features (Conservative Nature and reversibility in spite of having considerable variation) by using information theoretic measures in connection with other measures. The evolution of this Random Generator is equivalent to the evolution of its probabilistic description in terms of probability distribution over blocks of different lengths. By getting the aid of simulations we will show the ability of this system to preserve normality during the process of coarse graining.

Authors and Affiliations

Amirahmad Nayyeri, Gholamhossein Dastghaibyfard

Keywords

Related Articles

Prediction by a Hybrid of Wavelet Transform and Long-Short-Term-Memory Neural Network

Data originating from some specific fields, for in-stance tourist arrivals, may exhibit a high degree of fluctuations as well as non-linear characteristics due to time varying behaviors. This paper proposes a new hybrid...

The SMH Algorithm : An Heuristic for Structural Matrix Computation in the Partial Least Square Path Modeling

The Structural equations modeling with latent’s variables (SEMLV) are a class of statistical methods for modeling the relationships between unobservable concepts called latent variables. In this type of model, each laten...

CMMI-DEV Implementation Simplified

With the advance technology and increase in customer requirements, software organizations pursue to reduce cost and increase productivity by using standards and best practices. The Capability Maturity Model Integration (...

Fusion of Biogeography based optimization and Artificial bee colony for identification of Natural Terrain Features

Swarm Intelligence techniques expedite the configuration and collimation of the remarkable ability of group members to reason and learn in an environment of contingency and corrigendum from their peers by sharing informa...

Framework Utilizing Machine Learning to Facilitate Gait Analysis as an Indicator of Vascular Dementia

Vascular dementia (VD), the second most common type of dementia, effects approximately 13.9 per cent of people over the age of 71 in the United States alone. 26% of individuals develop VD after being diagnosed with conge...

Download PDF file
  • EP ID EP261613
  • DOI 10.14569/IJACSA.2018.090144
  • Views 91
  • Downloads 0

How To Cite

Amirahmad Nayyeri, Gholamhossein Dastghaibyfard (2018). An Information Theoretic Analysis of Random Number Generator based on Cellular Automaton. International Journal of Advanced Computer Science & Applications, 9(1), 321-329. https://europub.co.uk/articles/-A-261613