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Random number generation and Quasi-Monte Carlo methods
  • H. Niederreiter
  • Mathematics, Computer Science
  • CBMS-NSF regional conference series in applied…
  • 1992
TLDR
Preface 1. Monte Carlo methods and Quasi-Monte Carlo methods 2. Lattice rules for numerical integration 3. Low-discrepancy point sets and sequences 4. Nets and (t,s)-sequences 5. Random numbers and pseudorandom numbers. Expand
  • 3,501
  • 353
Point sets and sequences with small discrepancy
A systematic theory of a class of point sets called (t, m, s)-nets and of a class of sequences called (t, s)-sequences is developed. On the basis of this theory, point sets and sequences inExpand
  • 547
  • 79
Probability and computing: randomized algorithms and probabilistic analysis
TLDR
Randomized algorithms (making random choices during their execution) play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communications networks and secure protocols. Expand
  • 945
  • 78
  • PDF
Low-discrepancy and low-dispersion sequences
Abstract We generalize and improve earlier constructions of low-discrepancy sequences by Sobol', Faure, and the author, thus obtaining sequences in the s-dimensional unit cube with the smallestExpand
  • 430
  • 45
Introduction to finite fields and their applications: List of Symbols
TLDR
The first part of this book presents an introduction to the theory of finite fields, with emphasis on those aspects that are relevant for applications, such as information theory, algebraic coding theory and cryptology. Expand
  • 1,033
  • 42
Finite Fields: Encyclopedia of Mathematics and Its Applications.
Mathematics encyclopedia. finite fields books on advanced galois theory mathoverflow. elementary theory encyclopedia of mathematics. pdf download finite fields encyclopedia of mathematics. finiteExpand
  • 910
  • 40
Quasi-Monte Carlo methods and pseudo-random numbers
CONTENTS
  • 756
  • 30
  • PDF
Implementation and tests of low-discrepancy sequences
TLDR
Low-discrepancy sequences are used for numerical integration, in simulation, and in related applications. Expand
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