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Abstraction of Linear Consensus Networks with Guaranteed Systemic Performance Measures
[article]
2017
arXiv
pre-print
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A proper abstraction of a large-scale linear consensus network with a dense coupling graph is one whose number of coupling links is proportional to its number of subsystems and its performance is comparable ...
First, the existence of abstractions of a given network is proven. Then, we present an efficient and fast algorithm for computing a proper abstraction of a given network. ...
LOCALIZED NETWORK ABSTRACTION Our methodology can be extended further to explore several interesting network design problems, such as partial or localized abstraction of a given large-scale consensus network ...
arXiv:1709.01150v1
fatcat:7xm7iwos55axzj63347uars4ce
Control Strategies of Human Interactive Robot Under Uncertain Environments
[chapter]
2011
Mobile Robots - Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator Training
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Models are abstractions of the real world. As such, they only partially model the underlying physical process of the subject. ...
Background Extended Information Filter SLAM (EIF-SLAM) estimates the positions of robot and landmarks by updating information matrix and information vector. ...
Control Strategies of Human Interactive Robot Under Uncertain Environments, Mobile Robots -Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator Training, Dr. ...
doi:10.5772/25508
fatcat:mu3ab3k6dfdhjofdtyvtbupyhy
Graph Summarization Methods and Applications: A Survey
[article]
2018
arXiv
pre-print
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This survey is a structured, comprehensive overview of the state-of-the-art methods for summarizing graph data. We first broach the motivation behind, and the challenges of, graph summarization. ...
Finally, we discuss applications of summarization on real-world graphs and conclude by describing some open problems in the field. ...
Connections to graph clustering, sparsification, and compression. ...
arXiv:1612.04883v3
fatcat:fhg2g5eldfdgfkzoqdmbfl5er4
Towards Unsupervised Deep Graph Structure Learning
[article]
2022
arXiv
pre-print
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In recent years, graph neural networks (GNNs) have emerged as a successful tool in a variety of graph-related applications. ...
Specifically, we generate a learning target from the original data as an "anchor graph", and use a contrastive loss to maximize the agreement between the anchor graph and the learned graph. ...
Abstracting with credit is permitted. ...
arXiv:2201.06367v1
fatcat:ew3msx6p6vc5hadgkryoixhyuq
Spectral-clustering approach to Lagrangian vortex detection
2016
Physical review. E
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We carry out the clustering on a weighted graph, with the weights measuring pairwise distances of fluid trajectories in the extended phase space of positions and time. ...
We then extract coherent vortices from the graph using tools from spectral graph theory. ...
Isolated points resulting from the graph sparsification are shown in white.(a) (b) (c) FIG. 7. ...
doi:10.1103/physreve.93.063107
pmid:27415358
fatcat:dv5a6z7lffa7pjfcisheh6jeqy
GRAND+: Scalable Graph Random Neural Networks
[article]
2022
arXiv
pre-print
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Graph neural networks (GNNs) have been widely adopted for semi-supervised learning on graphs. ...
In this work, we present a scalable and high-performance GNN framework GRAND+ for semi-supervised graph learning. ...
of paper abstracts. ...
arXiv:2203.06389v1
fatcat:vt27na7majg3bo6hatxzygiwvm
Visualizing Sensor Network Coverage with Location Uncertainty
[article]
2017
arXiv
pre-print
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We present an interactive visualization system for exploring the coverage in sensor networks with uncertain sensor locations. ...
In the field of graph drawing, Wang et al. ...
Abstract simplicial complex. ...
arXiv:1710.06925v1
fatcat:suvhtiu7tncolhoioat5ve4ruy
A Combined Multiple Model Adaptive Control Scheme and Its Application to Nonlinear Systems With Nonlinear Parameterization
2012
IEEE Transactions on Automatic Control
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-S., +, TAC March 2012 809-810
Extended
Controller Synthesis for Continuous Descriptor Systems. ...
M., +, TAC June 2012 1592-1597
Various Ways to Compute the Continuous-Discrete Extended Kalman Filter. ...
doi:10.1109/tac.2011.2176162
fatcat:2airdooti5fi7kmuozmodywcga
Comparison of acoustic quantification and Doppler echocardiography in assessment of left ventricular diastolic variables
1993
Heart
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2
Abstract It remains fundamentally unclear how to reprogram complex evolving systems. ...
Extended Extended Figure 8 . ...
matrices by only capturing graph density by assigning dense B-A graphs higher entropy than Erdös-Rényi (E-R) graphs. ...
doi:10.1136/hrt.70.5.448
pmid:8260277
pmcid:PMC1025358
fatcat:byo6tt6jgvabjmbxwgwyzqz7qe
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
[article]
2018
arXiv
pre-print
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To this end we performed experiments and validated the results on (1) a very large set of small graphs, (2) a number of larger networks with different topologies, and (3) biological networks from a widely ...
The colour green represents the overlapping of areas for each graph and each method. The graphs used are a set of benchmarking graphs in the literature 11 . Extended Figure 7 . ...
Extended Figure 3 . ...
arXiv:1709.05429v11
fatcat:hldyt3tygjcqtft543scvbaamm
Treemap: An O(log n) algorithm for indoor simultaneous localization and mapping
2006
Autonomous Robots
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A major future challenge will be uncertain data-association. ...
UDA stands for 'Uncertain Data Association'. A √ means the algorithm can handle landmarks with uncertain identity. A C means covariance is available for performing χ 2 tests. ...
doi:10.1007/s10514-006-9043-2
fatcat:pww3nmtyqzaafmca4rfyzsoq7u
Effective Social Graph Deanonymization Based on Graph Structure and Descriptive Information
2015
ACM Transactions on Intelligent Systems and Technology
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Effective social graph deanonymization based on graph structure and descriptive information. ...
email dataset, and a social graph with millions of nodes from Tencent Weibo. ...
Abstracting with credit is permitted. ...
doi:10.1145/2700836
fatcat:g6yvs2xx5rfkzarvrkkaun7z5i
Reinforcement learning algorithms with function approximation: Recent advances and applications
2014
Information Sciences
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graph Laplacian. ...
The algorithms can also be extended to use eligibility traces [73, 120] . 2.6. ...
doi:10.1016/j.ins.2013.08.037
fatcat:ki77nykp6rabdmq2jxk3zvwlpm
Video Saliency Detection by using an Enhance Methodology Involving a Combination of 3DCNN with Histograms
2022
International Journal of Computers Communications & Control
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Video saliency detection has received a lot of attention in recent decades, but due to challenging temporal abstraction and fusion for spatial saliency, computational modelling of spatial perception for ...
In future we will extend the same patters on still image special and temporal saliency detection which is merely challenge task. ...
Graph for proposed and existing methods from DAVIS Dataset
Figure 9 : 9 Figure 9: Obtained F-measured values graph of proposed and existing methods fromSegtrckV2 Dataset
Table 1 : 1 Showing the ...
doi:10.15837/ijccc.2022.2.4299
fatcat:oqfxztbfyvbllclhgyxqbdj7ce
Factor Graphs for Robot Perception
2017
Foundations and Trends in Robotics
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They provide a powerful abstraction that gives insight into particular inference problems, making it easier to think about and design solutions, and write modular software to perform the actual inference ...
Finally, we provide an overview of applications of factor graphs for robot perception, showing the broad impact factor graphs had in robot perception. ...
[146] recently extended this approach by adding a convex optimization to better approximate nonlinear measurement functions throughout the sparsification. ...
doi:10.1561/2300000043
fatcat:flxlfe5aerg7ha4zasswzerj3e
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