Identificación de comportamiento fractal en generador de números aleatorios basado en memristor

Abstract

The behaviors of some natural physical phenomena are treated as complex systems. The weather, the probability distribution function of electrographic signals or stock exchange prices in economy present long – range dependence. The random number generation can be used to emulate these processes. For this reason, it is interesting to use the memristor features to generate random numbers. According to the above, the investigation object is to identify the presence of long – range dependence and fractal behavior in a random number generator based on memristor. To achieve it, it exposes to different chaotic systems based on memristor to construct the generator. Later, it estimates the Hurst parameter for long-range dependence detection and it is identified the fractality type of data synthesized. Finally, it makes a comparison between the model proposed and beta-MWM algorithm. The results show that the data synthesized have a variable Hurst parameter and monofractal – multifractal behavior. The main contribution of this investigation is the proposal of a new model to trace synthesis with long – range dependence and fractal behavior based on no – linearity of memristor.