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Abstraction of Linear Consensus Networks with Guaranteed Systemic Performance Measures [article]

Milad Siami, Nader Motee
2017 arXiv   pre-print
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]

Haiwei Dong, Zhiwei Luo
2011 Mobile Robots - Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator Training  
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]

Yike Liu, Tara Safavi, Abhilash Dighe, Danai Koutra
2018 arXiv   pre-print
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]

Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, Shirui Pan
2022 arXiv   pre-print
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

Alireza Hadjighasem, Daniel Karrasch, Hiroshi Teramoto, George Haller
2016 Physical review. E  
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]

Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang
2022 arXiv   pre-print
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]

Tim Sodergren, Jessica Hair, Jeff M. Phillips, Bei Wang
2017 arXiv   pre-print
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

Weitian Chen, Brian D. O. Anderson
2012 IEEE Transactions on Automatic Control  
-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

A Chenzbraun, F J Pinto, S Popylisen, I Schnittger, R L Popp
1993 Heart  
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]

Hector Zenil, Narsis A. Kiani, Francesco Marabita, Yue Deng, Szabolcs Elias, Angelika Schmidt, Gordon Ball, Jesper Tegnér
2018 arXiv   pre-print
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

Udo Frese
2006 Autonomous Robots  
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

Hao Fu, Aston Zhang, Xing Xie
2015 ACM Transactions on Intelligent Systems and Technology  
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

Xin Xu, Lei Zuo, Zhenhua Huang
2014 Information Sciences  
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

Suresh Kumar R, Mahalakshmi P, Jothilakshmi R, Kavitha M S, Balamuralitharan S
2022 International Journal of Computers Communications & Control  
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

Frank Dellaert, Michael Kaess
2017 Foundations and Trends in Robotics  
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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