In:
Technical Sciences, Uniwersytet Warminsko-Mazurski, , No. 2021 ( 2021-12-06)
Abstract:
Pseudo-random number generation techniques are an essential tool to correctly test machine learning processes. The methodologies are many, but also the possibilities to combine them in a new way are plenty. Thus, there is a chance to create mechanisms potentially useful in new and better generators. In this paper, we present a new pseudo-random number generator based on a hybrid of two existing generators - a linear congruential method and a delayed Fibonacci technique. We demonstrate the implementation of the generator by checking its correctness and properties using chi-square, Kolmogorov and TestU01.1.2.3 tests and we apply the Monte Carlo Cross Validation method in classification context to test the performance of the generator in practice.
Type of Medium:
Online Resource
ISSN:
2083-4527
,
1505-4675
Language:
Unknown
Publisher:
Uniwersytet Warminsko-Mazurski
Publication Date:
2021
detail.hit.zdb_id:
2406481-6