A Numerical Study of New Logistic Map

2018 ◽  
Vol 17 (02) ◽  
pp. 1871001
Author(s):  
Youssef Khmou
Keyword(s):  
Traffic Flow ◽  
Bifurcation Diagram ◽  
Random Number ◽  
Numerical Study ◽  
Random Sequence ◽  
Logistic Map ◽  
Growth Parameter ◽  
Random Number Generation ◽  
Macroscopic Model ◽  
Optimal Velocity

In this paper, we propose a new logistic map based on the relation of the information entropy, we study the bifurcation diagram comparatively to the standard logistic map. In the first part, we compare the obtained diagram, by numerical simulations, with that of the standard logistic map. It is found that the structures of both diagrams are similar where the range of the growth parameter is restricted to the interval [0,e]. In the second part, we present an application of the proposed map in traffic flow using macroscopic model. It is found that the bifurcation diagram is an exact model of the Greenberg’s model of traffic flow where the growth parameter corresponds to the optimal velocity and the random sequence corresponds to the density. In the last part, we present a second possible application of the proposed map which consists of random number generation. The results of the analysis show that the excluded initial values of the sequences are (0,1).

scholarly journals True Random Number Generation from Bioelectrical and Physical Signals

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Seda Arslan Tuncer ◽  
Turgay Kaya
Keyword(s):  
Blood Volume ◽  
Random Number ◽  
Logistic Map ◽  
Random Number Generation ◽  
Statistical Properties ◽  
Random Numbers ◽  
Number Generation ◽  
Skin Response ◽  
Volume Pulse ◽  
Blood Volume Pulse

It is possible to generate personally identifiable random numbers to be used in some particular applications, such as authentication and key generation. This study presents the true random number generation from bioelectrical signals like EEG, EMG, and EOG and physical signals, such as blood volume pulse, GSR (Galvanic Skin Response), and respiration. The signals used in the random number generation were taken from BNCIHORIZON2020 databases. Random number generation was performed from fifteen different signals (four from EEG, EMG, and EOG and one from respiration, GSR, and blood volume pulse datasets). For this purpose, each signal was first normalized and then sampled. The sampling was achieved by using a nonperiodic and chaotic logistic map. Then, XOR postprocessing was applied to improve the statistical properties of the sampled numbers. NIST SP 800-22 was used to observe the statistical properties of the numbers obtained, the scale index was used to determine the degree of nonperiodicity, and the autocorrelation tests were used to monitor the 0-1 variation of numbers. The numbers produced from bioelectrical and physical signals were successful in all tests. As a result, it has been shown that it is possible to generate personally identifiable real random numbers from both bioelectrical and physical signals.

Generalized delayed logistic map suitable for pseudo-random number generation

2015 ◽  
Author(s):  
Samar M. Ismail ◽  
Lobna A. Said ◽  
Ahmed G. Radwan ◽  
Ahmed H. Madian ◽  
Mohamed F. Abu-ElYazeed ◽  
...  
Keyword(s):  
Random Number ◽  
Logistic Map ◽  
Random Number Generation ◽  
Number Generation ◽  
Pseudo Random Number

scholarly journals Sensor-Seeded Cryptographically Secure Random Number Generation

2019 ◽  
Vol 8 (3) ◽  
pp. 1854-1857
Keyword(s):  
Random Number ◽  
Random Sequence ◽  
Random Number Generation ◽  
Sensor Data ◽  
Random Numbers ◽  
Pseudorandom Number Generator ◽  
Random Number Generators ◽  
Secret Keys ◽  
Initialization Vector ◽  
Entropy Source

Random numbers are essential to generate secret keys, initialization vector, one-time pads, sequence number for packets in network and many other applications. Though there are many Pseudo Random Number Generators available they are not suitable for highly secure applications that require high quality randomness. This paper proposes a cryptographically secure pseudorandom number generator with its entropy source from sensor housed on mobile devices. The sensor data are processed in 3-step approach to generate random sequence which in turn fed to Advanced Encryption Standard algorithm as random key to generate cryptographically secure random numbers.

A NUMERICAL STUDY OF UNIVERSALITY AND SELF-SIMILARITY IN SOME FAMILIES OF FORCED LOGISTIC MAPS

2013 ◽  
Vol 23 (04) ◽  
pp. 1350072 ◽  
Author(s):  
PAU RABASSA ◽  
ÀNGEL JORBA ◽  
JOAN CARLES TATJER
Keyword(s):  
Bifurcation Diagram ◽  
Numerical Study ◽  
Logistic Map ◽  
Finite Sequence ◽  
Invariant Curves ◽  
Self Similarity ◽  
Consecutive Period ◽  
Parametric Families ◽  
The One ◽  
Parameter Values

We explore different two-parametric families of quasi-periodically Forced Logistic Maps looking for universality and self-similarity properties. In the bifurcation diagram of the one-dimensional Logistic Map, it is well known that there exist parameter values sn where the 2n-periodic orbit is superattracting. Moreover, these parameter values lay between the parameters corresponding to two consecutive period doublings. In the quasi-periodically Forced Logistic Maps, these points are replaced by invariant curves, that undergo a (finite) sequence of period doublings. In this work, we study numerically the presence of self-similarities in the bifurcation diagram of the invariant curves of these quasi-periodically Forced Logistic Maps. Our computations show a remarkable self-similarity for some of these families. We also show that this self-similarity cannot be extended to any quasi-periodic perturbation of the Logistic map.

Random Number Generation in Bilingual Balinese and German Students: Preliminary Findings from an Exploratory Cross-Cultural Study

2009 ◽  
Vol 109 (1) ◽  
pp. 61-75 ◽  
Author(s):  
Hans Strenge ◽  
Cokorda Bagus Jaya Lesmana ◽  
Luh Ketut Suryani
Keyword(s):  
Random Number ◽  
Random Sequence ◽  
Random Number Generation ◽  
Cross Cultural ◽  
Group Differences ◽  
Simple Task ◽  
Number Generation ◽  
Cross Cultural Study ◽  
Cultural Research ◽  
Ethnic Group Differences

Verbal random number generation is a procedurally simple task to assess executive function and appears ideally suited for the use under diverse settings in cross-cultural research. The objective of this study was to examine ethnic group differences between young adults in Bali (Indonesia) and Kiel (Germany). 50 bilingual healthy students, 30 Balinese and 20 Germans, attempted to generate a random sequence of the digits 1 to 9. In Balinese participants, randomization was done in Balinese (native language L1) and Indonesian (first foreign language L2), in German subjects in the German (L1) and English (L2) languages. 10 of 30 Balinese (33%), but no Germans, were unable to inhibit habitual counting in more than half of the responses. The Balinese produced significantly more nonrandom responses than the Germans with higher rates of counting and significantly less occurrence of the digits 2 and 3 in L1 compared with L2. Repetition and cycling behavior did not differ between the four languages. The findings highlight the importance of taking into account culture-bound psychosocial factors for Balinese individuals when administering and interpreting a random number generation test.

A Modified SSLPS Algorithm with Logistic Pseudo-Random Sequence Generator for Improving the Performance of Neka Power Plant

2015 ◽  
Vol 6 (1) ◽  
pp. 1-29
Author(s):  
Ahmad Mozaffari ◽  
Mehdi Emami ◽  
Nasser L. Azad ◽  
Alireza Fathi
Keyword(s):  
Mathematical Model ◽  
Power Plant ◽  
Power Systems ◽  
Power Plants ◽  
Large Scale ◽  
Numerical Study ◽  
Random Sequence ◽  
Chaotic Map ◽  
Logistic Map ◽  
Energetic Efficiency

Metaheuristic techniques have successfully contributed to the development and optimization of large-scale distributed power systems. The archived literature demonstrate that the modification or tuning of the parameters of specific metaheuristics can provide powerful tools suited for optimization of power plants with different types of constraints. In spite of the high potential of metaheuristics in dealing with such systems, most of the conducted researches only address the optimization of the electrical aspects of power systems. In this research, the authors intend to attest the applicability of metaheuristics for optimizing the mechanical aspects of a real-world large-scale power plant, i.e. Neka power plant sited in Mazandaran, Iran. To do so, firstly, based on the laws of thermodynamics and the physics of the problem at hand, the authors implement a mathematical model to calculate the values of exergetic efficiency, energetic efficiency, and total cost of the Neka power plant as three main objective functions. Besides, a memetic supervised neural network and Bahadori's mathematical model are used to calculate the dynamic values of specific heat over the operating procedure of the power plant. At the second stage, a modified version of a recent spotlighted Pareto based multiobjective metaheuristic called synchronous self-learning Pareto strategy (SSLPS) is proposed. The proposed technique is based on embedding logistic chaotic map into the algorithmic architecture of SSLPS. In this context, the resulting optimizer, i.e. chaos-enhanced SSLPS (C-SSLPS), uses the response of time-discrete nonlinear logistic map to update the positions of heuristic agents over the optimization procedure. For the sake of comparison, strength Pareto evolutionary algorithm (SPEA 2), non-dominated sorting genetic algorithm (NSGA-II) and standard SSLPS are taken into account. The results of the numerical study confirm the superiority of the proposed technique as compared to the other rival optimizers. Besides, it is observed that metaheuristics can be successfully used for optimizing the mechanical/energetic parameters of Neka power plant.

Random Number Generation Based on the Rossler Attractor

2014 ◽  
Vol 1 ◽  
pp. 272-275 ◽  
Author(s):  
Vincent Canals ◽  
Antoni Morro ◽  
Josep L. Rosselló
Keyword(s):  
Random Number ◽  
Random Number Generation ◽  
Number Generation
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