Results 11 to 20 of about 7,855,956 (309)
A Review of Distributed Algorithms for Principal Component Analysis
Proceedings of the IEEE, 2018 Principal component analysis (PCA) is a fundamental primitive of many data analysis, array processing, and machine learning methods. In applications where extremely large arrays of data are involved, particularly in distributed data acquisition systems ...
Anna Scaglione +2 more
exaly +2 more sources
Distributed greedy pursuit algorithms [PDF]
Signal Processing, 2014 For compressed sensing over arbitrarily connected networks, we consider the problem of estimating underlying sparse signals in a distributed manner. We introduce a new signal model that helps to describe inter-signal correlation among connected nodes.
Mikael Skoglund +2 more
exaly +3 more sources
IEEE Transactions on Automation Science and Engineering, 2019 In this paper, a modified centralized algorithm based on particle swarm optimization (MCPSO) is presented to solve the task allocation problem in the search and rescue domain.
Xianfang Song, Paul Chung, Na Geng
exaly +2 more sources
Computing Handbook, 3rd ed., 2014 The new edition of a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often
Dan Alistarh, R. Guerraoui
semanticscholar +4 more sources
Asynchronous Activity Detection for Cell-Free Massive MIMO: From Centralized to Distributed Algorithms [PDF]
IEEE Transactions on Wireless Communications, 2022 Device activity detection in the emerging cell-free massive multiple-input multiple-output (MIMO) systems has been recognized as a crucial task in machine-type communications, in which multiple access points (APs) jointly identify the active devices from
Yang Li +4 more
semanticscholar +1 more source
Finite-Bit Quantization for Distributed Algorithms With Linear Convergence [PDF]
IEEE Transactions on Information Theory, 2021 This paper studies distributed algorithms for (strongly convex) composite optimization problems over mesh networks, subject to quantized communications. Instead of focusing on a specific algorithmic design, a black-box model is proposed, casting linearly
Chang-Shen Lee +2 more
semanticscholar +1 more source
A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems
IEEE Transactions on Smart Grid, 2017 Steven Low +2 more
exaly +2 more sources
Sensors, 2023 Within the scope of the ongoing efforts to fight climate change, the application of multi-robot systems to environmental mapping and monitoring missions is a prominent approach aimed at increasing exploration efficiency.
Chiara Ercolani +2 more
doaj +1 more source
Distributed Algorithms for Composite Optimization: Unified Framework and Convergence Analysis [PDF]
IEEE Transactions on Signal Processing, 2020 We study distributed composite optimization over networks: agents minimize a sum of smooth (strongly) convex functions–the agents’ sum-utility–plus a nonsmooth (extended-valued) convex one.
Jinming Xu +3 more
semanticscholar +1 more source
Information-Driven Gas Distribution Mapping for Autonomous Mobile Robots
Sensors, 2023 The ability to sense airborne pollutants with mobile robots provides a valuable asset for domains such as industrial safety and environmental monitoring.
Andres Gongora +5 more
doaj +1 more source