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1

Crunk, Anthony Wayne. "A portable C random number generator." Thesis, Virginia Tech, 1985. http://hdl.handle.net/10919/45720.

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Proliferation of computers with varying word sizes has led to increases in software use where random number generation is required. Several techniques have been developed. Criteria of randomness, portability, period, reproducibility, variety, speed, and storage are used to evaluate developed generation methods. The Tausworthe method is the only method to meet the portability requirement, and is chosen to be implemented. A C language implementation is proposed as a possible implementation and test results are presented to confirm the acceptability of the proposed code.<br>Master of Science
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Hörmann, Wolfgang, and Gerhard Derflinger. "A portable uniform random number generator well suited for the rejection method." Institut für Statistik und Mathematik, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 1992. http://epub.wu.ac.at/1288/1/document.pdf.

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Up to now all known efficient portable implementations of linear congruential random number generators with modulus 2^(31)-1 are working only with multipliers which are small compared with the modulus. We show that for non-uniform distributions, the rejection method may generate random numbers of bad quality if combined with a linear congruential generator with small multiplier. Therefore a method is described that works for any multiplier smaller than 2^(30). It uses the decomposition of multiplier and seed in high order and low order bits to compute the upper and the lower half of the produc
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Gautham, Smitha. "An Efficient Implementation of an Exponential Random Number Generator in a Field Programmable Gate Array (FPGA)." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2173.

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Many physical, biological, ecological and behavioral events occur at times and rates that are exponentially distributed. Modeling these systems requires simulators that can accurately generate a large quantity of exponentially distributed random numbers, which is a computationally intensive task. To improve the performance of these simulators, one approach is to move portions of the computationally inefficient simulation tasks from software to custom hardware implemented in Field Programmable Gate Arrays (FPGAs). In this work, we study efficient FPGA implementations of exponentially dist
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Jíra, Roman. "Generování náhodných čísel pomocí magnetických nanostruktur." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-232088.

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Random number generation can be based on physical events with probabilistic character, or on algorithms that use complex or one-way functions, alternatively on both of these approaches. A magnetic vortex is a basic state of magnetization that forms in magnetic micro- and nanostructures of an appropriate shape, dimensions and material. Quantities of the magnetic vortex form randomly if ambient conditions are chosen eligibly. A concept of a true random number generator using a random switching of states of the magnetic vortex is presented in this thesis. This concept is realized and random numbe
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Michálek, Tomáš. "Efektivní generátor náhodných čísel v nízko-výkonových zařízení." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-317140.

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This thesis solves the problem of generating random numbers on low-power devices. Author describes possible ways of generating and implements selected generators of (pseudo)random numbers on MSP430F5438A. 4 generators were added by the enhancement of one of them and a new generator was created, using the phenomenon of temperature change in the surroundings. For each generator, test sequences were generated and these sequences were tested by the Dieharder, STS-NIST, and Visual Test. The output of the thesis is the functional implementation of the generators, their testing by statistical methods
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Matoušek, Jiří. "Network Traffic Simulation and Generation." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-412835.

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Development of computer networks able to operate at the speed of 10 Gb/s imposes new requirements on newly developed network devices and also on a process of their testing. Such devices are tested by replaying synthetic or previously captured network traffic on an input link of the tested device. We must be able to perform both tasks also at full wire speed. Current testing devices are either not able to operate at the speed of 10 Gb/s or they are too expensive. Therefore, the aim of this thesis is to design and implement a hardware accelerated application able to generate and replay network t
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Karanam, Shashi Prashanth. "Tiny true random number generator." Fairfax, VA : George Mason University, 2009. http://hdl.handle.net/1920/4587.

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Thesis (M.S.)--George Mason University, 2009.<br>Vita: p. 91. Thesis director: Jens-Peter Kaps. Submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Engineering. Title from PDF t.p. (viewed Oct. 12, 2009). Includes bibliographical references (p. 88-90). Also issued in print.
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Narayanan, Ramaswamy Karthik. "ROLLBACK-ABLE RANDOM NUMBER GENERATORS FOR THE SYNCHRONOUS PARALLEL ENVIRONMENT FOR EMULATION AND DISCRETE-EVENT SIMULATION (SPE." Master's thesis, University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4352.

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Random Numbers form the heart and soul of a discrete-event simulation system. There are few situations where the actions of the entities in the process being simulated can be completely predicted in advance. The real world processes are more probabilistic than deterministic. Hence, such chances are represented in the system by using various statistical models, like random number generators. These random number generators can be used to represent a various number of factors, such as length of the queue. However, simulations have grown in size and are sometimes required to run on multiple machin
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AMINO, ROBERT, and JONI BAITAR. "Probabilistic Pseudo-random Number Generators." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157351.

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Random numbers are essential in many computer applications and games. The goal of this report is to examine two of the most commonly used random number generators and try to determine some of their strengths and weaknesses. These generators are the Linear Congruential Generator(LCG) and the Mersenne Twister(MT). The main objective will be to determine which one of these is the most optimal for low intensive usage and everyday work. Although some of the test results were in conclusive,there were some indications that MT is the better Pseudorandom Number Generator (PRNG) and therefore the prefer
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Xu, Xiaoke. "Benchmarking the power of empirical tests for random number generators." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B41508464.

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Kasikara, Gulin. "Progresses In Parallel Random Number Generators." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606651/index.pdf.

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Monte Carlo simulations are embarrassingly parallel in nature, so having a parallel and efficient random number generator becomes crucial. To have a parallel generator with uncorrelated processors, parallelization methods are implemented together with a binary tree mapping. Although, this method has considerable advantages, because of the constraints arising from the binary tree structure, a situation defined as problem of falling off the tree occurs. In this thesis, a new spawning method that is based on binary tree traversal and new spawn processor appointment is proposed to use when falling
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Franco, Juan. "Rapid Prototyping and Design of a Fast Random Number Generator." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc115036/.

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Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. the core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable. the fundamental hurdle is that digital computers cannot generate truly random numbers because the states and transitions of digital systems are well understood and predictable. Nothing in a digital computer happens truly randomly. Digital computers are sequential machines that perform a current state and
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Franco, Juan. "Rapid Prototyping and Design of a Fast Random Number Generator." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc115040/.

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Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. the core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable. the fundamental hurdle is that digital computers cannot generate truly random numbers because the states and transitions of digital systems are well understood and predictable. Nothing in a digital computer happens truly randomly. Digital computers are sequential machines that perform a current state and
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Martinez, Florette. "Mathematical studies of arithmetical pseudo-random numbers generators." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS222.

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Les générateurs de nombres pseudo-aléatoires linéaires sont faciles à comprendre et à mettre en œuvre. Le plus célèbre d'entre eux est le générateur congruentiel linéaire . Dans la première partie de cette thèse, nous présentons ce générateur et les différents algorithmes de récupération de clés qui ont été conçus contre lui depuis les années soixante-dix. Parce que ce générateur est simple, il a été utilisé pour concevoir des générateurs plus complexes et potentiellement cryptographiquement sûrs comme le Générateur Congruentiel Permuté (présenté et attaqué dans le chapitre 3) et Trifork (prés
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Bang, Jung Woong. "An Empirical Comparison of Random Number Generators: Period, Structure, Correlation, Density, and Efficiency." Thesis, University of North Texas, 1995. https://digital.library.unt.edu/ark:/67531/metadc277807/.

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Random number generators (RNGs) are widely used in conducting Monte Carlo simulation studies, which are important in the field of statistics for comparing power, mean differences, or distribution shapes between statistical approaches. Statistical results, however, may differ when different random number generators are used. Often older methods have been blindly used with no understanding of their limitations. Many random functions supplied with computers today have been found to be comparatively unsatisfactory. In this study, five multiplicative linear congruential generators (MLCGs) were chos
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Abellán, Sánchez Carlos. "Quantum random number generators for industrial applications." Doctoral thesis, Universitat Politècnica de Catalunya, 2018. http://hdl.handle.net/10803/587190.

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Randomness is one of the most intriguing, inspiring and debated topics in the history of the world. It appears every time we wonder about our existence, about the way we are, e.g. Do we have free will? Is evolution a result of chance? It is also present in any attempt to understand our anchoring to the universe, and about the rules behind the universe itself, e.g. Why are we here and when and why did all this start? Is the universe deterministic or does unpredictability exist? Remarkably, randomness also plays a central role in the information era and technology. Random digits are used in comm
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Tso, Chi-wai, and 曹志煒. "Stringency of tests for random number generators." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B29748367.

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Raffaelli, Francesco. "Quantum random number generators in integrated photonics." Thesis, University of Bristol, 2019. http://hdl.handle.net/1983/b20b0798-755d-4a57-843f-3951805e9f53.

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Random numbers find applications in a range of different fields, from quantum key distribution and classical cryptography to fundamental science. They also find extensive use in gambling and lotteries. By exploiting the probabilistic nature of Quantum Mechanics, quantum random number generators (QRNGs) provide a secure and efficient means to produce random numbers. Most of the quantum random number generators demonstrated so far have been built in bulk optics, either using free space or fibre-optic components. While showing good performance, most of these demonstrations are strongly limited in
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Ruhault, Sylvain. "Security analysis for pseudo-random number generators." Thesis, Paris, Ecole normale supérieure, 2015. http://www.theses.fr/2015ENSU0014/document.

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La génération d’aléa joue un rôle fondamental en cryptographie et en sécurité. Des nombres aléatoires sont nécessaires pour la production de clés cryptographiques ou de vecteurs d’initialisation et permettent également d’assurer que des protocoles d’échange de clé atteignent un niveau de sécurité satisfaisant. Dans la pratique, les bits aléatoires sont générés par un processus de génération de nombre dit pseudo-aléatoire, et dans ce cas, la sécurité finale du système dépend de manière cruciale de la qualité des bits produits par le générateur. Malgré cela, les générateurs utilisés en pratique
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Mitchum, Sam. "Digital Implementation of a True Random Number Generator." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2327.

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Random numbers are important for gaming, simulation and cryptography. Random numbers have been generated using analog circuitry. Two problems exist with using analog circuits in a digital design: (1) analog components require an analog circuit designer to insure proper structure and functionality and (2) analog components are not easily transmigrated into a different fabrication technology. This paper proposes a class of random number generators that are constructed using only digital components and typical digital design methodology. The proposed classification is called divergent path si
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Epstein, Peter Carleton University Dissertation Computer Science. "Generating geometric objects at random." Ottawa, 1992.

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Lian, Guinan. "Testing Primitive Polynomials for Generalized Feedback Shift Register Random Number Generators." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd1131.pdf.

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Gärtner, Joel. "Analysis of Entropy Usage in Random Number Generators." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214567.

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Cryptographically secure random number generators usually require an outside seed to be initialized. Other solutions instead use a continuous entropy stream to ensure that the internal state of the generator always remains unpredictable. This thesis analyses four such generators with entropy inputs. Furthermore, different ways to estimate entropy is presented and a new method useful for the generator analysis is developed. The developed entropy estimator performs well in tests and is used to analyse entropy gathered from the different generators. Furthermore, all the analysed generators exhibi
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Korsbakke, Andreas, and Robin Ringsell. "Promestra Security compared with other random number generators." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18238.

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Background. Being able to trust cryptographic algorithms is a crucial part of society today, because of all the information that is gathered by companies all over the world. With this thesis, we want to help both Promestra AB and potential future customers to evaluate if you can trust their random number generator. Objectives. The main objective for the study is to compare the random number generator in Promestra security with the help of the test suite made by the NationalInstitute of Standards and Technology. The comparison will be made with other random number generators such as Mersenne Tw
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Bisadi, Zahra. "All-Silicon-Based Photonic Quantum Random Number Generators." Doctoral thesis, University of Trento, 2017. http://eprints-phd.biblio.unitn.it/2603/1/ZAHRA_BISADI_Thesis.pdf.

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Random numbers are fundamental elements in different fields of science and technology such as computer simulation like Monte Carlo-method simulation, statistical sampling, cryptography, games and gambling, and other areas where unpredictable results are necessary. Random number generators (RNG) are generally classified as “pseudo”-random number generators (PRNG) and "truly" random number generators (TRNG). Pseudo random numbers are generated by computer algorithms with a (random) seed and a specific formula. The random numbers produced in this way (with a small degree of unpredictability) are
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Yadav, Avantika. "Design and Analysis of Digital True Random Number Generator." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3229.

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Random number generator is a key component for strengthening and securing the confidentiality of electronic communications. Random number generators can be divided as either pseudo random number generators or true random number generators. A pseudo random number generator produces a stream of numbers that appears to be random but actually follow predefined sequence. A true random number generator produces a stream of unpredictable numbers that have no defined pattern. There has been growing interest to design true random number generator in past few years. Several Field Programmable Gate Array
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Xu, Xiaoke, and 許小珂. "Benchmarking the power of empirical tests for random numbergenerators." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41508464.

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L'Ecuyer, Pierre, and Josef Leydold. "rstream: Streams of Random Numbers for Stochastic Simulation." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 2005. http://epub.wu.ac.at/1544/1/document.pdf.

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The package rstream provides a unified interface to streams of random numbers for the R statistical computing language. Features are: * independent streams of random numbers * substreams * easy handling of streams (initialize, reset) * antithetic random variates The paper describes this packages and demonstrates an simple example the usefulness of this approach.<br>Series: Preprint Series / Department of Applied Statistics and Data Processing
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Pilcher, Martha Geraldine. "Development and validation of random cut test problem generator." Diss., Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/24560.

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Mattioli, Federico. "Testing a Random Number Generator: formal properties and automotive application." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18187/.

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L'elaborato analizza un metodo di validazione dei generatori di numeri casuali (RNG), utilizzati per garantire la sicurezza dei moderni sistemi automotive. Il primo capitolo fornisce una panoramica della struttura di comunicazione dei moderni autoveicoli attraverso l'utilizzo di centraline (ECU): vengono riportati i principali punti di accesso ad un automobile, assieme a possibili tipologie di hacking; viene poi descritto l'utilizzo dei numeri casuali in crittografia, con particolare riferimento a quella utilizzata nei veicoli. Il secondo capitolo riporta le basi di probabilità necessarie a
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Gutenberg, Lukas, and Emil Olin. "Generation of random numbers from the text found in tweets." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-283043.

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Random numbers are integral to many areas of computer science, it is used in everything from video games to encryption of important messages and simulations. These numbers are often generated by mathematical algorithms and it is highly important for these generators to generate numbers that are truly random and unpredictable, as patterns, cycles or other discrepancies might at worst cause serious security flaws that can be exploited. Random numbers can also be generated with the aid of a source of entropy, for this report the source used was the text found on the social media site Twitter to s
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Hörmann, Wolfgang. "The generation of binomial random variates." Institut für Statistik und Mathematik, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 1992. http://epub.wu.ac.at/1242/1/document.pdf.

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The transformed rejection method, a combination of inversion and rejection, which can be applied to various continuous distributions, is well suited to generate binomial random variates as well. The resulting algorithms are simple and fast, and need only a short set-up. Among the many possible variants two algorithms are described and tested: BTRS a short but nevertheless fast rejection algorithm and BTRD which is more complicated as the idea of decomposition is utilized. For BTRD the average number of uniforms required to return one binomial deviate lies between 2.5 and 1.4 which is considera
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Saiprasert, Chalermpol. "Design exploration of an FPGA-based multivariate Gaussian random number generator." Thesis, Imperial College London, 2010. http://hdl.handle.net/10044/1/6212.

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Monte Carlo simulation is one of the most widely used techniques for computationally intensive simulations in a variety of applications including mathematical analysis and modeling and statistical physics. A multivariate Gaussian random number generator (MVGRNG) is one of the main building blocks of such a system. Field Programmable Gate Arrays (FPGAs) are gaining increased popularity as an alternative means to the traditional general purpose processors targeting the acceleration of the computationally expensive random number generator block due to their fine grain parallelism and reconfigurab
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Petura, Oto. "True random number generators for cryptography : Design, securing and evaluation." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSES053.

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Les nombres aléatoires sont essentiels pour les systèmes cryptographiques modernes. Ils servent de clés cryptographiques, de nonces, de vecteurs d’initialisation et de masques aléatoires pour la protection contre les attaques par canaux cachés. Dans cette thèse, nous traitons des générateurs de nombres aléatoires dans les circuits logiques (FPGA et ASIC). Nous présentons les méthodes fondamentales de génération de nombres aléatoires dans des circuits logiques. Ensuite, nous discutons de différents types de TRNG en utilisant le jitter d’horloge comme source d’aléa. Nous faisons une évaluation r
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Pareschi, Fabio <1976&gt. "Chaos-based random number generators: monolithic implementation, testing and applications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2007. http://amsdottorato.unibo.it/467/1/PhDThesis-Pareschi_Chaos-based_random_number_generatos.pdf.

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Pareschi, Fabio <1976&gt. "Chaos-based random number generators: monolithic implementation, testing and applications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2007. http://amsdottorato.unibo.it/467/.

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Ben, Romdhane Molka. "Modélisation, implémentation et caractérisation de circuits générateurs de nombres aléatoires vrais pour la certification de crypto-processeurs." Thesis, Paris, ENST, 2014. http://www.theses.fr/2014ENST0055/document.

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Les nombres aléatoires sont indispensables dans de nombreuses applications notamment en cryptographie où l’aléa est utilisé dans les protocoles de sécurité. Les générateurs de nombres aléatoires, plus connus sous le nom de RNG comme “Random Number Generator” se déclinent en deux familles, les PRNG (Pseudo RNG) qui sont des générateurs de nombres aléatoires ayant des séquences déterministes et les TRNG (True RNG) qui sont des générateurs d’aléa “vrai”, donc non prédictibles. Les applications cryptographiques utilisent à la fois les TRNG et les PRNG. Un PRNG nécessite une valeur initiale, ou gra
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Dusitsin, Krid, and Kurt Kosbar. "Accuracy of Computer Simulations that use Common Pseudo-random Number Generators." International Foundation for Telemetering, 1998. http://hdl.handle.net/10150/609238.

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International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California<br>In computer simulations of communication systems, linear congruential generators and shift registers are typically used to model noise and data sources. These generators are often assumed to be close to ideal (i.e. delta correlated), and an insignificant source of error in the simulation results. The samples generated by these algorithms have non-ideal autocorrelation functions, which may cause a non-uniform distribution in the data or noise sign
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Stockis, Jean-Pierre. "On some problems related to machine-generated noise." Thesis, University of Kent, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263694.

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Shanmuga, Sundaram Prassanna. "Development of a FPGA-based True Random Number Generator for Space Applications." Thesis, Linköping University, Electronics System, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54534.

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<p>Random numbers are required for cryptographic applications such as IT security products, smart cards etc. Hardwarebased random number generators are widely employed. Cryptographic algorithms are implemented on FieldProgrammable Gate Arrays (FPGAs). In this work a True Random Number Generator (TRNG) employed for spaceapplication was designed, investigated and evaluated. Several cryptographic requirements has to be satisfied for therandom numbers. Two different noise sources was designed and implemented on the FPGA. The first design wasbased on ring oscillators as a noise source. The second d
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Bakiri, Mohammed. "Hardware implementation of a pseudo random number generator based on chaotic iteration." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCD014/document.

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La sécurité et la cryptographie sont des éléments clés pour les dispositifs soumis à des contraintes comme l’IOT, Carte à Puce, Systèm Embarqué, etc. Leur implémentation matérielle constitue un défi en termes de limitation en ressources physiques, vitesse de fonctionnement, capacité de mémoire, etc. Dans ce contexte, comme la plupart des protocoles s’appuient sur la sécurité d’un bon générateur de nombres aléatoires, considéré comme un élément indispensable dans le noyau de sécurité. Par conséquent, le présent travail propose des nouveaux générateurs pseudo-aléatoires basés sur des itérations
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42

Krempa, Peter. "Analysis of Entropy Levels in the Entropy Pool of Random Number Generator." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236179.

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V informatice je pojem entropie obvykle znám jako nahodný proud dat.  Tato práce krátce shrnuje metody generovaní nahodných dat a popisuje generátor náhodnych čísel, jež je obsažen v jádře operačního systému Linux.  Dále se práce zabývá určením bitové rychlosti generování nahodných dat tímto generátorem ve virtualizovaném prosředí, které poskytují různé hypervizory.  Práce popíše problémy nízkého výkonu generátory nahodných dat ve virtualním prostředí a navrhne postup pro jejich řešení.  Poté je nastíňena implementace navržených postupů, které je podrobena testům a její vysledky jsou porovnány
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43

Yang, Chunxiao. "Fractional chaotic pseudo-random number generator design and application to image cryptosystem." Electronic Thesis or Diss., Ecole centrale de Nantes, 2022. http://www.theses.fr/2022ECDN0063.

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Dans cette thèse, nous avons utilisé des systèmes chaotiques pour concevoir des générateurs de nombres pseudoaléatoires(PRNG) et appliqué ces derniers aux cryptosystèmes en raison de leurs caractéristiques prometteuses, telles que le caractèrealéatoire et la sensibilité aux conditions initiales. Les systèmes chaotiques fractionnaires, bien que moins discutés que les carteset systèmes chaotiques classiques d’ordre entier, possèdent une complexité inhérente qui apporte de la nouveauté, de la complexité et des clés secrètes supplémentaires à la conception Chaotic PRNG (CPRNG), qui à son tour amél
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Alice, Reinaudo. "Empirical testing of pseudo random number generators based on elliptic curves." Thesis, Linnéuniversitetet, Institutionen för matematik (MA), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-44875.

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An introduction on random numbers, their history and applications is given, along with explanations of different methods currently used to generate them. Such generators can be of different kinds, and in particular they can be based on physical systems or algorithmic procedures. The latter type of procedures gives rise to pseudo-random number generators. Specifically, several such generators which are based on elliptic curves are examined. Therefore, in order to ease understanding, a basic primer on elliptic curves over fields and the operations arising from their group structure is also provi
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Hörmann, Wolfgang. "A Universal Generator for Bivariate Log-Concave Distributions." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 1995. http://epub.wu.ac.at/1044/1/document.pdf.

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Different universal (also called automatic or black-box) methods have been suggested to sample from univariate log-concave distributions. The description of a universal generator for bivariate distributions has not been published up to now. The new algorithm for bivariate log-concave distributions is based on the method of transformed density rejection. In order to construct a hat function for a rejection algorithm the bivariate density is transformed by the logarithm into a concave function. Then it is possible to construct a dominating function by taking the minimum of several tangent planes
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Ritchie, Robert Peter. "Efficient Constructions for Deterministic Parallel Random Number Generators and Quantum Key Distribution." Miami University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=miami1619099112895031.

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Zouhar, Petr. "Generátor náhodných čísel." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218290.

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The thesis deals with issues of random numbers, their generating and use in cryptography. Introduction of work is aimed to resolution of random number generators and pseudo--random number generators. There is also included often used dividing generators on software and hardware. We mention advantages and disadvantages of each type and area of their use. Then we describe examples of random and pseudorandom numbers, mainly hardware based on physical phenomenon such as the decay of radioactive material or use atmospheric noise. The following part is devoted to suggestion own random number generat
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Grigaravičienė, Milda. "Pseudoatsitiktinių skaičių generatorių statistinių savybių tyrimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2006. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2006~D_20060605_212214-88087.

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Pseudorandom number generator‘s statistical features were analyzed in this work. Pseudorandom numbers are applied in many fields, that‘s why it‘s important for them to satisfy following requirements: • to have uniform distribution, • to be uncorrelated. Hypothesis that random numbers are distributed uniformly is checked by Pearson test. Hypothesis that autocorrelation function is equal to zero is checked by Box Ljung test. During investigation it was noticed, that in all ways generated random numbers didn’t have uniform distribution, except linear congriuential generator. Applying different tr
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Aponte, Erick. "A Study on Energy Harvesters for Physical Unclonable Functions and Random Number Generation." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78673.

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As the broad implementation and use of wireless sensor nodes in Internet of Things (IOT) devices increase over the years, securing personal data becomes a growing issue. Physical unclonable functions (PUFs) and random number generators (RNGs) provide methods to generate security keys for data encryption. Transducers used in the energy harvesting systems of wireless sensor nodes, can generate the PUFs and RNGs. These transducers include piezoelectric devices (piezo), thermoelectric generators (TEG) and solar cells. This research studies the electrical properties of transducers at normal and
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Leydold, Josef, Hannes Leeb, and Wolfgang Hörmann. "Higher-Dimensional Properties of Non-Uniform Pseudo-Random Variates." Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business, 1998. http://epub.wu.ac.at/268/1/document.pdf.

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In this paper we present the results of a first empirical investigation on how the quality of non-uniform variates is influenced by the underlying uniform RNG and the transformation method used. We use well known standard RNGs and transformation methods to the normal distribution as examples. We find that except for transformed density rejection methods, which do not seem to introduce any additional defects, the quality of the underlying uniform RNG can be both increased and decreased by transformations to non-uniform distributions. (author's abstract)<br>Series: Preprint Series / Department o
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