Voronoi Projection-Based Fast Nearest-Neighbor Search Algorithms: Box-Search and Mapping Table-Based Search Techniques

Ramasubramanian, V.; Paliwal, Kuldip K.

doi:10.1006/dspr.1997.0300

Cited by 7 publications

(4 citation statements)

References 42 publications

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“…A 2D Voronoi diagram is a useful tool to perform fast diagnosis [25][26][27][28]. The Voronoi partition permits the search to be viewed geometrically as a point location problem of determining which region contains the target Figure 5.…”

Section: Fdd By Employing Voronoi Diagramsmentioning

confidence: 99%

Miniaturized sensors for intelligent system fault detection and diagnosis (FDD)

Kao

Zhang

2007

SPIE Proceedings

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Intelligent fault detection and diagnosis (FDD) depends on smart sensors which not only can render sensory information but also can make easy the subsequent detection and diagnosis. At the heart of every intelligent FDD system, there are sensors which work collaboratively with one another as well as the intelligent system. Miniaturized sensors present unique advantages in facilitating the installation of sensory devices for the purpose of diagnosis. In this paper, we present ongoing research on intelligent FDD and characterization using miniaturized sensor. With miniaturization, sensors can be readily made and integrated into intelligent diagnosis. Characterization and modeling of such innovative sensor designs are presented. Using new smart multi-function, telemetric, and integrated sensors as "intelligent nodes" in systems will provide necessary sensory information (for example, an integrated sensor which measures pressure, flow, and temperature-all in one module). The characterization and studies of miniaturized sensor are presented, with practical relevance to applications. The concept of intelligent nodes is further augmented with wireless sensors and system integration.

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Section: Fdd By Employing Voronoi Diagramsmentioning

confidence: 99%

Miniaturized sensors for intelligent system fault detection and diagnosis (FDD)

Kao

Zhang

2007

SPIE Proceedings

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“…To avoid traversing wrong direction paths, projectionbased VQ approaches [20][21][22][23][24] have been proposed. Most of these approaches applied principal component analysis (PCA) to preserve most information of data, which is called the ratio of preserved information.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

“…Finally, other existing VQ algorithms were compared with the proposed approach. Chang and Wu [24] showed that PVDS outperforms other approaches such as DTPC [20], SCS [21], TSVQ [31], and HOSM [32]; therefore, PVDS was chosen as the baseline approach. Because the proposed approach involved applying a binary search algorithm based on 2D projection and Voronoi vertices to find an initial codeword, the number of dimensions for Voronoi diagram must be less than 3.…”

Section: Comparisons With Othermentioning

confidence: 99%

A Hybrid Vector Quantization Combining a Tree Structure and a Voronoi Diagram

Chen

2014

Mathematical Problems in Engineering

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Multimedia data is a popular communication medium, but requires substantial storage space and network bandwidth. Vector quantization (VQ) is suitable for multimedia data applications because of its simple architecture, fast decoding ability, and high compression rate. Full-search VQ can typically be used to determine optimal codewords, but requires considerable computational time and resources. In this study, a hybrid VQ combining a tree structure and a Voronoi diagram is proposed to improve VQ efficiency. To efficiently reduce the search space, a tree structure integrated with principal component analysis is proposed, to rapidly determine an initial codeword in low-dimensional space. To increase accuracy, a Voronoi diagram is applied to precisely enlarge the search space by modeling relations between each codeword. This enables an optimal codeword to be efficiently identified by rippling an optimal neighbor from parts of neighboring Voronoi regions. The experimental results demonstrated that the proposed approach improved VQ performance, outperforming other approaches. The proposed approach also satisfies the requirements of handheld device application, namely, the use of limited memory and network bandwidth, when a suitable number of dimensions in principal component analysis is selected.

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“…There are several methods to compute the Voronoi and its dual the Delaunay tessellations (Watson, 1981;Bowyer, 1981;Ramasubramanian and Paliwal, 1997). Perhaps one of the more successful approaches is the one based on representation in an extended space by mapping the instances in R n+1 , and attempting to search their convex hull.…”

Section: Introductionmentioning

confidence: 99%

Efficient Computation of Voronoi Neighbors Based on Polytope Search in Pattern Recognition

Méndez¹,

Lorenzo²

2012

Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods

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Some algorithms in Pattern Recognition and Machine Learning as neighborhood-based classification and dataset condensation can be improved with the use of Voronoi tessellation. The paper shows the weakness of some existing algorithms of tessellation to deal with high dimensional datasets. The use of linear programming can improve the tessellation procedures by focusing in Voronoi adjacency. It will be shown that the adjacency test based on linear programming is a version of the polytope search. However, the polytope search procedure provides more information than a simple Boolean test. The paper proposes a strategy to use the additional information contained in the basis of the linear programming algorithm to obtain other tests. The theoretical results are applied to tessellate several random datasets, and also for much-used datasets in Machine Learning repositories.

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Voronoi Projection-Based Fast Nearest-Neighbor Search Algorithms: Box-Search and Mapping Table-Based Search Techniques

Cited by 7 publications

References 42 publications

Miniaturized sensors for intelligent system fault detection and diagnosis (FDD)

Miniaturized sensors for intelligent system fault detection and diagnosis (FDD)

A Hybrid Vector Quantization Combining a Tree Structure and a Voronoi Diagram

Efficient Computation of Voronoi Neighbors Based on Polytope Search in Pattern Recognition

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