Showing papers on "Decision tree model published in 1978"

A data structure for orthogonal range queries

Abstract: Given a set of points in a d-dimensional space, an orthogonal range query is a request for the number of points in a specified d-dimensional box. We present a data structure and algorithm which enable one to insert and delete points and to perform orthogonal range queries. The worstcase time complexity for n operations is O(n logd n); the space usea is O(n logd-1 n). (O-notation here is with respect to n; the constant is allowed to depend on d.) Next we briefly discuss decision tree bounds on the complexity of orthogonal range queries. We show that a decision tree of height O(dn log n) (Where the implied constant does not depend on d or n) can be constructed to process n operations in d dimensions. This suggests that the standard decision tree model will not provide a useful method for investigating the complexity of such problems.

On the complexity of computing the measure of ∪[ai,bi]

Abstract: The decision tree complexity of computing the measure of the union of n (possibly overlapping) intervals is shown to be O(n log n), even if comparisons between linear functions of the interval endpoints are allowed. The existence of an O(n log n) lower bound to determine whether any two of n real numbers are within ∈ of each other is also demonstrated. These problems provide an excellent opportunity for discussing the effects of the computational model on the ease of analysis and on the results produced.