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Can I read The Mean Square Discrepancy of Randomized Nets on EtoBox?
The Mean Square Discrepancy of Randomized Nets by Fred J. Hickernell is a Computer Science article available to read on EtoBox.
What is The Mean Square Discrepancy of Randomized Nets about?
One popular family of low dicrepancy sets is the ( __t, m, s__ )-nets. Recently a randomization of these nets that preserves their net property has been introduced. In this article a formula for the mean square __L__ ^2^ -discrepancy of ( __0, m, s__ )-nets in base __b__ is derived. This formula has a computational complexity of only O(s log( __N__ ) + s ^2^ ) for large __N__ or s, where __N = b ^m^__ is the number of points. Moreover, the root mean square __L__ ^2^ -discrepancy of ( __0, m, s__ )-nets is show to be O( __N__ ^-1^ [log(N)] ^(s-1)/2^ ) as __N__ tends to infinity, the same asymptotic order as the known lower bound for the __L__ ^2^ -discrepancy of an arbitrary set.
Who reads The Mean Square Discrepancy of Randomized Nets?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Fred J. Hickernell
- Publisher
- ACM
- Published
- 1996
- Language
- EN
- Field
- Computer Science (Physical Sciences)