Protocol-Based Non-Fragile State Estimation for Delayed Recurrent Neural Networks Subject to Replay Attacks
Fan Yang, Hongli Dong, Yuxuan Shen, Xuerong Li, Dongyan Dai
Abstract
Dear Editor, This letter focuses on the protocol-based non-fragile state estimation problem for a class of recurrent neural networks (RNNs). With the development of communication technology, the networked systems have received particular attentions. The networked system brings advantages such as easy to implement, high flexibility as well as low cost, and also has disadvantages such as limited bandwidth of the communication network which lead to networked-induced phenomena [1], [2]. To alleviate the network-induced phenomena, communication protocols have been introduced in the communication networks of the networked systems [3], [4]. As a widely used communication protocol in real practice, the round-robin (RR) protocol has received research interest and the state estimation problem under the RR protocol is an on-going hotspot in the area of signal processing [5]. Nevertheless, for the RNNs, the corresponding RR protocol-based state estimation problem still needs further research effort which is the first motivation of this letter.