Yayik, ApdullahKutlu, Yakup2024-09-182024-09-182013978-1-4673-5563-6978-1-4673-5562-92165-0608https://hdl.handle.net/20.500.12483/1125621st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUSPseudo-random number generators generate sequent of digits that cannot be expected before. Random number generators are used in lots of studies especially physical and statical implementations. In this paper; by using Multi-Layer Perceptron Neural Network, a traditional random number generator is strengthened. In the end of the study; both of random number generators are tested by some randomness tests of National Institute of Standard Technology test suite. As a result, it is learned that Neural Networks can generate good random numbers.trinfo:eu-repo/semantics/closedAccessMulti-Layer PerceptronNeural NetworksPseudo Random Number GeneratorsConference Object2-s2.0-84880868534N/AWOS:000325005300334N/A