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Siyong Song

dblp:339/6093 · DBLP profile ↗
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4ranked-venue papers
2as first author
4since 2021 · last 2026
0009-0009-2793-9791ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems
networked control systems
0.712023
Stochastic stabilization of Markovian jump systems closed by a communication network: an auxiliary system approach · Sci. China Inf. Sci. 2023
Mathematical optimization › control theory › optimal control
stochastic control
0.712023
Stochastic stabilization of Markovian jump systems closed by a communication network: an auxiliary system approach · Sci. China Inf. Sci. 2023

Methods — techniques the papers use, named apart from their topics

auxiliary system approach · 1.3
YearPublicationVenuePosition
2026 K-Means Mode-Clustered Like-Fuzzy Control for Stochastic Markovian Jump Systems and Its Application to DoS Attacks
Siyong Song, Yingchun Wang 0003, Fei Teng 0004, Huaguang Zhang
IEEE Trans Autom. Sci. Eng.1
2026 Mode Cluster-Based Event-Triggered Control for Stochastic Markovian Jump Systems Under Denial-of-Service Attack
abstract
This article investigates the mode cluster-based event-triggered control (MCETC) of stochastic Markovian jump systems (SMJSs) under denial-of-service (DoS) attack. First, a novel MCETC framework is designed by considering the interplay among subsystems, DoS attacks, and the event-triggered mechanism (ETM). In this framework, the controller mode is reconstructed, and the number of controller modes is reduced by reclustering the system modes. It significantly reduces the conservatism of the system compared to existing mode-dependent/-independent controllers. Second, a switching ETM is designed for scenarios with and without DoS attack activation, which can effectively save network bandwidth resources and reduce computational load. Third, a multi-Lyapunov function based on DoS attacks is proposed to ensure the stability of the closed-loop SMJSs. Then, the controller gains and event-triggered parameters are jointly solved via the linear matrix inequality (LMI) technique. Moreover, the maximum allowable sampling interval (MASI) is given such that the controller can restore the control signals as soon as a DoS attack ends, which enables faster stabilization of the closed-loop system. Finally, a numerical example is used to verify the effectiveness and superiority of the proposed method.
Siyong Song, Yingchun Wang 0003, Jiayue Sun, Yunfei Mu
IEEE Trans. Cybern.1
2024 Stabilization of stochastic systems with sampled-state feedback controllers
Siyong Song, Yande Zhang
Inf. Sci.2
2023 Stochastic stabilization of Markovian jump systems closed by a communication network: an auxiliary system approach
Siyong Song
Sci. China Inf. Sci.2