Zobrazeno 1 - 10
of 1 015
pro vyhledávání: '"Ding, Steven X."'
Autor:
Chen, Zhiwen, Mo, Siwen, Ke, Haobin, Ding, Steven X., Jiang, Zhaohui, Yang, Chunhua, Gui, Weihua
Learning representations of two views of data such that the resulting representations are highly linearly correlated is appealing in machine learning. In this paper, we present a canonical correlation guided learning framework, which allows to be rea
Externí odkaz:
http://arxiv.org/abs/2409.19396
This paper is concerned with the detection, resilient and fault-tolerant control issues for cyber-physical systems. To this end, the impairment of system dynamics caused by the defined types of cyber-attacks and process faults is analyzed. Then, the
Externí odkaz:
http://arxiv.org/abs/2409.13370
Autor:
Ding, Steven X., Li, Linlin
In this draft, fault diagnosis in nonlinear dynamic systems is addressed. The objective of this work is to establish a framework, in which not only model-based but also data-driven and machine learning based fault diagnosis strategies can be uniforml
Externí odkaz:
http://arxiv.org/abs/2309.02732
The replay attack detection problem is studied from a new perspective based on parity space method in this paper. The proposed detection methods have the ability to distinguish system fault and replay attack, handle both input and output data replay,
Externí odkaz:
http://arxiv.org/abs/2306.02020
This paper is dedicated to control theoretically explainable application of autoencoders to optimal fault detection in nonlinear dynamic systems. Autoencoder-based learning is a standard machine learning method and widely applied for fault (anomaly)
Externí odkaz:
http://arxiv.org/abs/2208.01291
Publikováno v:
In Reliability Engineering and System Safety November 2024 251
Publikováno v:
In Information Sciences September 2024 678