首页|Findings from Guangzhou University Provide New Insights into Machine Learning (S tability Analysis of Networked Control Systems Under Dos Attacks and Security Co ntroller Design With Mini-batch Machine Learning Supervision)
Findings from Guangzhou University Provide New Insights into Machine Learning (S tability Analysis of Networked Control Systems Under Dos Attacks and Security Co ntroller Design With Mini-batch Machine Learning Supervision)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting out of Guangzhou, People’s Republic of China, by NewsRx editors, research stated, “This study investigates the stability problem in nonlinear networked control systems (NCSs). First, inno vative compression rules are introduced to mitigate network congestion and bandw idth utilization issues stemming from quality of service (QoS) queuing mechanism s and denial of service (DoS) attacks.” Financial support for this research came from National Key Research and Developm ent Plan. Our news journalists obtained a quote from the research from Guangzhou Universit y, “We develop an intelligent trigger controller supervised by a mini-batch mach ine learning (MBML) algorithm to optimize network bandwidth utilization. Further more, we formulate more generalized Lyapunov-Krasovskii functions (LKFs) to simp lify mathematical derivations, and we employ appropriate integral inequalities t o minimize constraints.”
GuangzhouPeople’s Republic of ChinaA siaCybersecurityCyborgsEmerging TechnologiesMachine LearningGuangzhou University
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