Optimal Tree of a Complete Weighted Graph

Author(s):  
Seyed Soheil Hosseini ◽  
Nick Wormald ◽  
Tianhai Tian
Keyword(s):  
2020 ◽  
Vol 964 (10) ◽  
pp. 49-58
Author(s):  
V.I. Bilan ◽  
A.N. Grigor’ev ◽  
G.G. Dmitrikov ◽  
E.A. Dudin

The direction of research on the development of a scientific and methodological tool for the analysis of spatial objects in order to determine their generalized spatial parameters was selected. An approach to the problem of modeling networks and groups of objects based on the synthesis of a weighted graph is proposed. The spatial configuration of objects based on the given conditions is described by a weighted graph, the edge length of which is considered as the weight of the edges. A generalization to the typical structure of a spatial graph is formulated; its essence is representation of nodal elements as two-dimensional (polygonal) objects. To take into account the restrictions on the convergence of the vertices described by the buffer zones, a complementary graph is formed. An algorithm for constructing the implementation of a spatial object based on the sequential determination of vertices that comply with the given conditions is proposed. Using the software implementation of the developed algorithm, an experiment was performed to evaluate the spatial parameters of the simulated objects described by typical graph structures. The following parameters were investigated as spatial ones


2021 ◽  
pp. 1-1
Author(s):  
Tianjiao Wang ◽  
Xinyu Wang ◽  
Zengfu Wang ◽  
Chao Guo ◽  
William Moran ◽  
...  

Author(s):  
Guang-Yu Zhang ◽  
Xiao-Wei Chen ◽  
Yu-Ren Zhou ◽  
Chang-Dong Wang ◽  
Dong Huang ◽  
...  

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1231
Author(s):  
Yunbo Shi ◽  
Juanjuan Zhang ◽  
Jingjing Jiao ◽  
Rui Zhao ◽  
Huiliang Cao

High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.


Author(s):  
Xue Mei ◽  
Weiwei Li ◽  
Ryad Chellali ◽  
Yu Zhou ◽  
Jiashuang Huang ◽  
...  

1992 ◽  
Vol 02 (01) ◽  
pp. 31-41 ◽  
Author(s):  
PILAR DE LA TORRE ◽  
RAYMOND GREENLAW ◽  
TERESA M. PRZYTYCKA

This paper places the optimal tree ranking problem in [Formula: see text]. A ranking is a labeling of the nodes with natural numbers such that if nodes u and v have the same label then there exists another node with a greater label on the path between them. An optimal ranking is a ranking in which the largest label assigned to any node is as small as possible among all rankings. An O(n) sequential algorithm is known. Researchers have speculated that this problem is P-complete. We show that for an n-node tree, one can compute an optimal ranking in O( log n) time using n2/ log n CREW PRAM processors. In fact, our ranking is super critical in that the label assigned to each node is absolutely as small as possible. We achieve these results by showing that a more general problem, which we call the super critical numbering problem, is in [Formula: see text]. No [Formula: see text] algorithm for the super critical tree ranking problem, approximate or otherwise, was previously known; the only known [Formula: see text] algorithm for optimal tree ranking was an approximate one.


Algorithmica ◽  
2014 ◽  
Vol 72 (2) ◽  
pp. 369-378 ◽  
Author(s):  
Erik D. Demaine ◽  
John Iacono ◽  
Stefan Langerman

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