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Trends in Applied Sciences Research
  Year: 2012 | Volume: 7 | Issue: 1 | Page No.: 96-102
DOI: 10.17311/tasr.2012.96.102
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Fuzzy Cellular Automata Based Random Numbers Generation

Ramin Ayanzadeh, Azam S. Zavar Mousavi and Ehsan Shahamatnia

Due to the steady increasing trend toward computer simulations, generating random numbers has attracted many researches and several techniques have been introduced in recent years. In this study by employing fuzzy operators on the structure of cellular automata update rules a new approach has been proposed for uniformly distributed random number generation. The simulation results show that the uniformity of the proposed method is very promising. The nature of this approach also makes it very suitable for hardware implementation.
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  •    Central Limit Theorem based Cellular Automata for Generating Normal Random Numbers
  •    Dynamic Parameters Optimization for Enhancing Performance and Stability of PSO
  •    Discrete Time Dynamic Neural Networks for Predicting Chaotic Time Series
  •    Fuzzy Honey Bees Foraging Optimization: Swarm Intelligence Approach for Clustering
  •    Honey Bees Foraging Optimization for Mixed Nash Equilibrium Estimation
  •    Determining Optimum Queue Length in Computer Networks by Using Memetic Algorithms
  •    Innovative Approach to Generate Uniform Random Numbers Based on a Novel Cellular Automata
  •    A Novel Design for Quantum-dot Cellular Automata Cells and Full Adders
How to cite this article:

Ramin Ayanzadeh, Azam S. Zavar Mousavi and Ehsan Shahamatnia, 2012. Fuzzy Cellular Automata Based Random Numbers Generation. Trends in Applied Sciences Research, 7: 96-102.

DOI: 10.17311/tasr.2012.96.102






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