Catálogo de publicaciones - libros
Python Scripting for Computational Science
Hans Petter Langtangen
Second Edition.
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
Computational Science and Engineering; Numerical and Computational Physics; Software Engineering/Programming and Operating Systems; Computational Intelligence
Disponibilidad
| Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | 2006 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-3-540-29415-3
ISBN electrónico
978-3-540-31269-7
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2006
Información sobre derechos de publicación
© Springer-Verlag Berlin Heidelberg 2006
Cobertura temática
Tabla de contenidos
More Advanced GUI Programming
Hans Petter Langtangen
We address the problem of detecting deviations of a binary sequence from randomness, which is very important for ra ndom number (RNA) and pseudorandom number generators (PRNG) and their applications to cryptography. Namely, we consider a hypothesis that a given bit sequence is generated by the Bernoulli source with equal probabilities of 0’s and 1’s and the alternative hypothesis that the sequence is generated by a stationary and ergodic source which differs from the source under . We show that data compression methods can be used as a basis for such testing and describe two new tests for randomness, which are based on ideas of universal coding. Known statistical tests and suggested ones are applied for testing PRNGs which are used in practice. The experiments show that the power of the new tests is greater than of many known algorithms.
Pp. 515-589
Tools and Examples
Hans Petter Langtangen
We address the problem of detecting deviations of a binary sequence from randomness, which is very important for ra ndom number (RNA) and pseudorandom number generators (PRNG) and their applications to cryptography. Namely, we consider a hypothesis that a given bit sequence is generated by the Bernoulli source with equal probabilities of 0’s and 1’s and the alternative hypothesis that the sequence is generated by a stationary and ergodic source which differs from the source under . We show that data compression methods can be used as a basis for such testing and describe two new tests for randomness, which are based on ideas of universal coding. Known statistical tests and suggested ones are applied for testing PRNGs which are used in practice. The experiments show that the power of the new tests is greater than of many known algorithms.
Pp. 591-662