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  • logn at ac.els-cdn.com
    An O(logn) parallel connectivity algorithm - ScienceDirect
    References. 1. D.S Hirschberg, A.K Chandra, D.V Sarwate. Computing connected components on parallel computers. Comm. ACM, 22 (No. 8) (1979), pp. 461– .
  • logn at www.nada.kth.se
    Division in O(logn) Depth Using O(n1+ ) Processors Warning: This is .
    2 logn) depth circuits for division with size O(n1+ ) for any > 0. The key improvement is that we are able to do Chinese remaindering with (n1+ ) processors in.
  • logn at www.corelab.ece.ntua.gr
    Elementary O(logN) Step Algorithms - Corelab
    Elementary O(logN) Step Algorithms. •Algorithms are optimal in terms of speed. Only matrix Algorithms are work efficient. •Routing sorting convolution use N2.
  • logn at www.cs.cornell.edu
    Binary search runs in O(logn) time.
    Binary search runs in O(logn) time. Michael George. Tuesday March 29, 2005. This is a proof that binary search runs in O(log n) time. Here is the code:.
  • logn at web.math.princeton.edu
    A (logn) integrality gap for the Sparsest Cut SDP
    A (logn). Ω(1) integrality gap for the Sparsest Cut SDP. Jeff Cheeger∗. Courant Institute. New York University. New York, USA. Email: [email protected]
  • logn at www.seas.upenn.edu
    Homework 2 solution - SEAS
    Posted 02/14/2003. Problem 1: (5 pts) We show that. 1. log(logn) = O(log2n). 2. log2 n = O(elogn). 3. elogn = O(log(n!)) 4. log(n!) = O((logn)logn. Part 1: lim n^´.
  • logn at hea-www.cfa.harvard.edu
    logN-logS
    9 Nov 2010 . log10(N>S)-log10(S) cumulative number of sources detectable at a given telescopic sensitivity. S = [ergs s-1 cm-2]. N = number of sources .

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  • Bex Logn
    Bex Logn, Curtin University Australia, Faculty of Humanities, Australia, Visual Arts, Visual Sociology and Communication and Media.

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