This paper delves into the design of an asynchronous Fault Detection Filter (FDF) for Singular Fuzzy Markovian Jump Systems (SFMJSs), particularly under the influence of multi-cyber-attacks, leveraging an enhanced adaptive event-triggered mechanism (AETM). Initially, a Hidden Markovian Model (HMM) is employed to characterize the asynchronous interactions between SFMJSs and FDF. Subsequently, a mode-dependent AETM alongside a dynamic quantization protocol is synergistically utilized to optimize communication bandwidth and augment data transmission efficiency. Additionally, the study introduces an expansive range of multi-cyber-attacks, encompassing deception, replay, and Denial-of-Service (DoS) attacks, to mirror inherent vulnerabilities in wireless signal transmission. Furthermore, the performance of the FDF error system is assessed within a comprehensive framework using Linear Matrix Inequalities (LMIs), guided by a generalized performance index. This research establishes innovative admissibility criteria and filter conditions, aimed at guaranteeing the feasibility of desired FDF gains and ensuring the exponential admissibility of the FDF error system, underpinned by a generalized performance index. This manuscript concludes with two illustrative examples to demonstrate the efficacy of the proposed methodologies.

中文翻译：

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针对多重网络攻击的奇异模糊马尔可夫跳跃系统改进的异步故障检测滤波器设计

本文深入研究了奇异模糊马尔可夫跳跃系统 (SFMJS) 的异步故障检测滤波器 (FDF) 的设计，特别是在多重网络攻击的影响下，利用增强型自适应事件触发机制 (AETM)。最初，采用隐马尔可夫模型 (HMM) 来表征 SFMJS 和 FDF 之间的异步交互。随后，协同利用模式相关的 AETM 和动态量化协议来优化通信带宽并提高数据传输效率。此外，该研究还引入了广泛的多重网络攻击，包括欺骗、重放和拒绝服务 (DoS) 攻击，以反映无线信号传输中固有的漏洞。此外，FDF 误差系统的性能是在广义性能指数的指导下，使用线性矩阵不等式 (LMI) 在综合框架内进行评估。这项研究建立了创新的容许标准和过滤条件，旨在保证所需 FDF 增益的可行性，并确保以广义性能指数为基础的 FDF 误差系统的指数容许性。本手稿最后以两个说明性示例来证明所提出方法的有效性。