Results 201 to 210 of about 11,341,287 (236)
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To what extent are multiple pendulum systems viable in pseudo-random number generation?
arXiv.orgThis paper explores the development and viability of an alternative pseudorandom number generator (PRNG) that leverages the chaotic dynamics of multiple pendulum systems.
Matthew Sigit
semanticscholar +1 more source
Monte Carlo simulation sensitivity to pseudorandom number generators in hosting capacity analysis
2025 17th Electrical Engineering Faculty Conference - Energetics and Efficiency (BulEF)In Monte Carlo studies, there are two key aspects that researchers must carefully consider: the pseudorandom number generation algorithm and the number of simulation runs. This study focuses on the impact of these factors on voltage deviation analysis in
Ivan Tonev, Nikolay Nikolaev
semanticscholar +1 more source
A method for generating normal pseudorandom numbers
Let \(x=x_ 1,x_ 2,...,x_ n\) be independent random variables uniformly distributed on \(\). Let \(A=\| a_{ij}\|\) be the orthogonal matrix of the n-dimensional Walsh transformation. Then AX is asymptotically (for \(n\to \infty)\) a vector of n independent normal random variables.Gut, R. Eh., Egorov, V. V., Il'in, V. N.
openaire +2 more sources
Deterministic random number generation: Pseudorandom number generator
AIP Conference ProceedingsDinesh Kumar Mouttoucoumaran +4 more
semanticscholar +1 more source
New methods for pseudorandom numbers and pseudorandom vector generation
Proceedings of the 24th conference on Winter simulation - WSC '92, 1992openaire +2 more sources
Evaluation of a Pseudorandom Normal Number Generator
Journal of the ACM, 1964openaire +3 more sources
Random number generation and Quasi-Monte Carlo methods
CBMS-NSF Regional Conference Series in Applied Mathematics, 1992H. Niederreiter
semanticscholar +1 more source
Pseudorandom vector generation by the inversive method
ACM Transactions on Modeling and Computer Simulation, 1994Richard E Nance
exaly