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Event-triggered gradient-based distributed optimisation for multi-agent systems with state consensus constraint

Aijuan Wang, Xiaofeng Liao, Tao Dong
2018 IET Control Theory & Applications  
This study focuses on the event-triggered gradient-based algorithm for a distributed optimisation problem of multiagent system subject to state consensus constraint over directed networks, where each agent  ...  A novel gradient-based optimisation consensus algorithm is proposed to solve the optimisation consensus problem, where the event-triggered strategy based on sample-data is employed.  ...  In [23] , the authors have proposed the zero-gradient-sum (ZGS) algorithms based on the event-triggered strategy for a distributed convex optimisation consensus problem. However, Qiu et al.  ... 
doi:10.1049/iet-cta.2017.0328 fatcat:7cbguuiykfb4nangwg2fiuejfy

Autonomous Mobility Management for 5G Ultra-Dense HetNets via Reinforcement Learning With Tile Coding Function Approximation

Qianyu Liu, Chiew Foong Kwong, Sijia Zhou, Tianhao Ye, Lincan Li, Saeid Pourroostaei Ardakani
2021 IEEE Access  
The authors of [8] develop an intelligent handover optimisation scheme based on Q-learning.  ...  In Section A, we first present the work on the handover parameter optimisation method, which aims to adjust HHM and TTT of the A3 event to trigger the handover process.  ... 
doi:10.1109/access.2021.3095555 fatcat:surok5uavfewrjzd6iraleprlu

Distributed node authentication in wireless sensor networks

Feng Yang, Xuehai Zhou
2010 2010 2nd International Conference on Future Computer and Communication  
This thesis investigates distributed network optimisation in three types of dynamic WSNs: WSNs powered by time-varying solar energy, WSNs with fluctuating wireless channel quality, and WSNs with mobile  ...  In distributed optimisation, sensor nodes communicate with each other to collaboratively solve the overall network optimisation problem.  ...  In slot i 2 , node 1 triggers a RI event (Δλ 1 = 5.5).  ... 
doi:10.1109/icfcc.2010.5497835 fatcat:cnuk5y3arjdxxkhhrpoksskuzm

Training Spiking Neural Networks Using Lessons From Deep Learning [article]

Jason K. Eshraghian and Max Ward and Emre Neftci and Xinxin Wang and Gregor Lenz and Girish Dwivedi and Mohammed Bennamoun and Doo Seok Jeong and Wei D. Lu
2022 arXiv   pre-print
The brain is the perfect place to look for inspiration to develop more efficient neural networks.  ...  Some ideas are well accepted and commonly used amongst the neuromorphic engineering community, while others are presented or justified for the first time here.  ...  for their support.  ... 
arXiv:2109.12894v4 fatcat:zujzdtzaijak5bklbqufrxr57q

Contention Based Proportional Fairness (CBPF) Transmission Scheme for Time Slotted Channel Hopping Networks [article]

Lokesh Bommisetty, TG Venkatesh
2021 arXiv   pre-print
In this paper, we propose a contention based proportional fairness (CBPF) transmission scheme for TSCH networks to maximize the system throughput addressing fair allocation of resources to the nodes.  ...  The proposed CBPF transmission scheme has been implemented in the IoT-LAB public testbed to evaluate its performance and to compare with the existing scheduling algorithms.  ...  Total delay experienced by a packet is the sum of its queuing delay and the service time.  ... 
arXiv:2112.07164v1 fatcat:hmvfpatuwbeyzdqra5hkbe3oa4

The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity [article]

Christian Pehle, Sebastian Billaudelle, Benjamin Cramer, Jakob Kaiser, Korbinian Schreiber, Yannik Stradmann, Johannes Weis, Aron Leibfried, Eric Müller, Johannes Schemmel
2022 arXiv   pre-print
It combines a custom analog accelerator core supporting the accelerated physical emulation of bio-inspired spiking neural network primitives with a tightly coupled digital processor and a digital event-routing  ...  While implementation details differ, spiking neural networks - sometimes referred to as the third generation of neural networks - are the common abstraction used to model computation with such systems.  ...  Mayr from TU Dresden for the PLL macro cell [84] and SerDes macros [85] used in the current BSS-2 chip revisions, and Tugba Demirci from EPFL Lausanne for the on-chip fast MADC.  ... 
arXiv:2201.11063v2 fatcat:5zniosxozzapjan3afpg6ywggi

The factored policy-gradient planner

Olivier Buffet, Douglas Aberdeen
2009 Artificial Intelligence  
That is, we optimise a parameterised policy using gradient ascent.  ...  This factored policy gradient (FPG) planner can optimise steps to goal, the probability of success, or attempt a combination of both.  ...  We also wish to thank the organisers of the IPC-5 probabilistic track for opportunity to test FPG and for the subsequent feedback.  ... 
doi:10.1016/j.artint.2008.11.008 fatcat:r5igklyeb5gklbqyvqza5ujj5a

Hybrid predictive control strategy for a public transport system with uncertain demand

Doris Sáez, Cristián E. Cortés, Freddy Milla, Alfredo Núñez, Alejandro Tirachini, Marcela Riquelme
2012 Transportmetrica  
associated with event k, zero otherwise.  ...  The network is a one-way loop route, with P equidistant stops and b buses running around the loop, under the control of the dispatcher.  ... 
doi:10.1080/18128601003615535 fatcat:nkgx76j2qbdfxilztwfoi3iixe

Distributed optimization in multi-user MIMO systems with imperfect and delayed information

Pierre Coucheney, Bruno Gaujal, Panayotis Mertikopoulos
2014 2014 IEEE International Symposium on Information Theory  
Starting from an entropy-driven reinforcement learning scheme for multi-agent environments, we develop a distributed algorithm for robust spectrum management in Gaussian multiple-input, multipleoutput  ...  , convergent algorithm in discrete time.  ...  shows that the discrete-time scheme (11) will converge to an approximate solution of (P), and the error ε(τ) of this approximation will tend to zero as τ → 0.  ... 
doi:10.1109/isit.2014.6875404 dblp:conf/isit/CoucheneyGM14 fatcat:l5zds3teibbzvf3gvsraqekbsm

On the impact of selected modern deep-learning techniques to the performance and celerity of classification models in an experimental high-energy physics use case [article]

Giles Chatham Strong
2020 arXiv   pre-print
Beginning from a basic neural-network architecture, we test the potential benefits offered by a range of advanced techniques for machine learning, in particular deep learning, in the context of a typical  ...  use with both GPU and CPU hardware setups.  ...  I would also like to thank Tommaso Dorigo and David Rousseau for the useful discussions, as well the two reviewers of the manuscript for their thorough and helpful recommendations.  ... 
arXiv:2002.01427v4 fatcat:zl7yezr2avbahn2lluplprow6a

Probabilistic Scheduling of UFLS to Secure Credible Contingencies in Low Inertia Systems [article]

Cormac O'Malley, Luis Badesa, Fei Teng, Goran Strbac
2021 arXiv   pre-print
This paper derives a novel nadir constraint from the swing equation that, for the first time, provides a framework for the optimal comparison of all these services.  ...  We demonstrate that this constraint can be accurately and conservatively approximated for moderate UFLS levels with a second order cone, resulting in highly tractable convex problems.  ...  The step change in demand reverts the frequency gradient to zero, thus the trigger level corresponds to the nadir.  ... 
arXiv:2103.06616v1 fatcat:y5mdhmz64jbr3ke7jmanajnvvy

AI and ML – Enablers for Beyond 5G Networks

Alexandros Kaloxylos, Anastasius Gavras, Daniel Camps Mur, Mir Ghoraishi, Halid Hrasnica
2020 Zenodo  
In the sequel the white paper elaborates on use case and optimisation problems that are being tackled with AI/ML, partitioned in three major areas, namely: network planning, network diagnostics/insights  ...  , and network optimisation and control.  ...  The other one [84] emphasises the schemes to allow vertical users to influence the run-time optimisation of their network slices.  ... 
doi:10.5281/zenodo.4299895 fatcat:ngzbopfm6bb43lnrmep6nz5icm

Performance Issues in Optical Burst/Packet Switching [chapter]

Davide Careglio, Javier Aracil, Siamak Azodolmolky, Joan García-Haro, Sebastian Gunreben, Guoqiang Hu, Mikel Izal, Andreas Kimsas, M. Klinkowski, Martin Köhn, Eduardo Magaña, Daniel Morató (+7 others)
2009 Lecture Notes in Computer Science  
It consists of an introduction, five sections with contributions on five different specific topics, and a final section dedicated to the conclusions.  ...  optimisation gradient methods [40] can be used.  ...  Numerical results We evaluated the performance of our routing scheme in an event-driven simulator.  ... 
doi:10.1007/978-3-642-01524-3_8 fatcat:vozuuja5zbaaliaaa4wxex6dai

A Comprehensive Overview of TCP Congestion Control in 5G Networks: Research Challenges and Future Perspectives

Josip Lorincz, Zvonimir Klarin, Julije Ožegović
2021 Sensors  
The fifth-generation (5G) mobile network presents a new challenge for the implementation of the TCP CC mechanism, since networks will operate in environments with huge user device density and vast traffic  ...  Moreover, the capabilities of machine learning technique implementations for the improvement of TCPs CC performance have been presented last, with a discussion on future research opportunities that can  ...  However, with the advent of 6G networks, ML will need to be considered as the dominant direction in the field of network CC. There are possible directions in the implementation of the ML for CC.  ... 
doi:10.3390/s21134510 pmid:34209431 pmcid:PMC8271918 fatcat:ibwmx74gmrhlppphxaeydqd6iu

The MEG detector for μ +→e+ γ decay search

J. Adam, X. Bai, A. M. Baldini, E. Baracchini, C. Bemporad, G. Boca, P. W. Cattaneo, G. Cavoto, F. Cei, C. Cerri, M. Corbo, N. Curalli (+68 others)
2013 European Physical Journal C: Particles and Fields  
The paper is completed with a description of the equipment and techniques developed for the calibration in time and energy and the simulation of the whole apparatus.  ...  , a timing counter for measuring the positron time, and a liquid xenon detector for measuring the photon energy, position and time.  ...  David Stoker of the University of California, Irvine, for his careful proofreading of the manuscript and its improvements.  ... 
doi:10.1140/epjc/s10052-013-2365-2 fatcat:ygo3rdnkrjd5hb4c2khlv6o5hq
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