Results 261 to 270 of about 1,069,691 (320)
Some of the next articles are maybe not open access.

Partitioning and separating sets of orthogonal polygons

Information Sciences, 1987
A geometrical object in the plane is said to be orthogonal if its edges are either vertical or horizontal. A polygon is called orthoconvex if for every vertical-or-horizontal segment, its two endpoints lying in the polygon implies the whole segment lying in the polygon.
Ottmann, Thomas   +2 more
openaire   +1 more source

A Lattice-Partition Framework of Downlink Non-Orthogonal Multiple Access Without SIC

IEEE Transactions on Communications, 2018
In this paper, a novel lattice-partition-based downlink non-orthogonal multiple access framework is proposed. This framework is motivated by recognizing the algebraic structure behind the previous scheme recently proposed by Shieh and Huang as a lattice ...
Min Qiu   +3 more
semanticscholar   +1 more source

Orthogonal Partitions in Designed Experiments

Designs, Codes and Cryptography, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Scheduling parallel implementations of partitioned orthogonal transformations

SPIE Proceedings, 1992
Orthogonal matrix transformations form an important part of matrix-based signal processing applications. Systolic arrays for computing these algorithms have been developed and the size of these arrays usually depends directly on the size of the problem.
Prashanth Kuchibhotla, Bhaskar D. Rao
openaire   +1 more source

Set-partition methods and orthogonal designs

2010 IEEE International Symposium on Information Theory, 2010
Space-time block codes based on orthogonal designs are useful from practical point of view as these codes admit symbol-by-symbol maximum-likelihood decoding and also achieve full diversity. Though the square orthogonal designs have been studied quite extensively, there is very little progress in the area of non-square orthogonal designs.
openaire   +1 more source

Partitioning Orthogonal Histograms into Rectangular Boxes

2018
The problem of partitioning an orthogonal polyhedron into a minimum number of boxes was shown to be NP-hard in 1991, but no approximability result is known except for a 4-approximation algorithm for 3D-histograms. In this paper we broaden the understanding of the 3D-histogram partitioning problem.
Therese Biedl   +5 more
openaire   +1 more source

New partitioning schemes for parallel modified Gram-Schmidt orthogonalization

Proceedings of the 1997 International Symposium on Parallel Architectures, Algorithms and Networks (I-SPAN'97), 2002
In this paper we are concerned with parallel implementation of row-oriented Gram-Schmidt orthogonalization. For the data partitioning four types of columnwise partitioning schemes were considered: column (1-col), block, cyclic and block-cyclic (b-c) partitioning.
S. Oliveria, T. Soma
openaire   +1 more source

Approximate partitioning of 2D objects into orthogonally convex components

Computer Vision and Image Understanding, 2013
A fast and efficient algorithm to obtain an orthogonally convex decomposition of a digital object is presented. The algorithm reports a sub-optimal solution and runs in O(nlogn) time for a hole-free object whose boundary consists of n pixels. The decomposition algorithm can, in fact, be applied on any hole-free orthogonal polygon; in our work, it is ...
Mousumi Dutt   +2 more
openaire   +1 more source

Computer simulation of the partitioning by mutually orthogonal lines

2019 IEEE 15th International Conference on the Experience of Designing and Application of CAD Systems (CADSM), 2019
The partitioning problem of areas into regions along mutually orthogonal lines is considered. A mathematical model of the problem has been proposed, taking into account economic, agrotechnical and fire prevention restrictions. A method has been developed for obtaining a local-optimal partition of a given region based on the construction of two ...
Valentina Komyak   +6 more
openaire   +1 more source

Home - About - Disclaimer - Privacy