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It provides the ability to navigate in a multidimensional data structure.
Octree is a type of multidimensional data structure with which a multidimensional data space is recursively divided into eight equal subspaces (namely quadrants) until a quadrant contains only one data object.
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Multidimensional data structures are of considerable interest in many fields, including computational geometry, computer graphics, and scientific data visualization.
For this reason, poly-spectra output multidimensional data structures which comprise redundant information, distributed in multi-dimensional geometries, often called tensors.
Researchers have proposed multidimensional data structures such as R-tree [5], Quadtree [6, 7], and Octree [8], all of which enable efficient performance in data storage and searching systems.
Berkeley Madonna offers multidimensional arrays as data structure.
We have also derived LR filters and LR detectors based on AU-HOSVD for multidimensional data containing one LR structure contribution.
In this paper, we use a multidimensional radix tree like data structure for storing paths in the discreted-dimensional space Zd.
We next derive LR filters and LR detectors based on AU-HOSVD for multidimensional data composed of one LR structure contribution.
Self-organizing maps (SOMs) are a type of artificial neural network (ANN) with unsupervised learning designed to examine the structure of multidimensional data.
The KDB-tree and its variants have been reported to have good performance by using them as the index structure for retrieving multidimensional data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com