Sentence examples for generation of pseudorandom numbers from inspiring English sources

In the present paper, MATLAB is used to describe algorithms for the generation of pseudorandom numbers with both uniform and normal distributions.

The study sample, from both clinical histories and stays for analysis, was obtained by simple randomness via computer generation of a table of pseudorandom numbers.

Random number streams are used to generate reproducible sequences of pseudorandom numbers.

Its security is dependent upon the length of pseudorandom numbers generated by two communication parties.

In this communication we introduce a one-PRNG-per-kernel-call-per-thread scheme, in which a micro-stream of pseudorandom numbers is generated in each thread and kernel call.

This architecture provides a spatially distributed set of pseudorandom numbers, which are required in the local non-deterministic decisions at the various sites in the lattice, using pseudorandom number generators based upon cellular automata.

This method represents an alternative choice to the use of pseudorandom numbers, provided that a special care is paid to keep sufficiently uncorrelated as well as uniform the former sequences.

Bartz [13] calls seeds antithetic: they are used to start up a sequence of pseudorandom numbers and can be used to reproduce the same sequence of numbers.

By taking advantage of the characteristics of pseudorandom number generators, this implementation eliminates global synchronization and reduces the overhead caused by interprocessor communication in replica exchange in PT.

Our algorithm views the system dynamics as a "black-box", i.e., we only require control of pseudorandom number generator inputs.

In particular, we extend a lattice test designed for this class of pseudorandom number generators to parts of the period and arbitrary lags and prove that these generators pass this test up to very high dimensions.