时滞忆阻神经网络的固定时间同步及其在保密通信中的应用

薛彦斌; 童东兵; 陈巧玉; 毛琦

doi:10.21656/1000-0887.450304

时滞忆阻神经网络的固定时间同步及其在保密通信中的应用

doi: 10.21656/1000-0887.450304

上海工程技术大学电子电气工程学院，上海 201620

基金项目:

国家自然科学基金 61673257

详细信息

作者简介:
薛彦斌(2000—), 男, 硕士生(E-mail: 2432921997@qq.com)

通讯作者:
童东兵(1979—), 男，教授，博士(通讯作者. E-mail: tongdb@sues.edu.cn)

中图分类号: O175.13
计量
- 文章访问数: 109
- HTML全文浏览量: 29
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2024-11-07
- 修回日期: 2025-04-18
- 刊出日期: 2025-12-01

Fixed-Time Synchronization of Time-Delayed Memristive Neural Networks With Application to Confidential Communication

School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, P.R.China

摘要

摘要: 针对具有时变时滞的忆阻神经网络，研究了其固定时间同步和在保密通信中的应用. 为了有效解决有限时间同步控制依赖初始条件的问题，利用Lyapunov稳定性理论，通过所设计的状态反馈控制器，得到了主从系统固定时间同步的充分条件和调整时间的上界. 在此基础上，以时滞忆阻神经网络为发射器，以响应系统为接收器，采用了混沌遮掩的方式实施信号加密，实现了在固定时间内恢复加密信号，确保了保密通信的安全性和时效性.
- 忆阻神经网络 /
- 固定时间同步 /
- 保密通信 /
- Lyapunov稳定性理论
Abstract: The fixed-time synchronization of time-delayed memristive neural networks and its application in confidential communication was studied. To effectively solve the problem of finite-time synchronization control relying on initial conditions, the Lyapunov stability theory was used to obtain sufficient conditions for fixed-time synchronization of the master-slave system and upper bounds for the settling time through the designed state feedback controller. On this basis, the time-delayed memristive neural network was taken as the transmitter and its response system as the receiver, and the signal encryption was implemented by means of chaotic masking, to enable the recovery of the encrypted signal within a fixed time and ensure the security and timeliness of confidential communication.
- memristive neural network /
- fixed-time synchronization /
- confidential communication /
- Lyapunov stability theory

HTML全文

图 1 保密通信流程

Figure 1. The confidential communication process

下载: 全尺寸图片幻灯片

图 2 控制器作用下的同步误差e(t)的轨迹

Figure 2. Trajectories of synchronization error e(t) under the action of the controller

下载: 全尺寸图片幻灯片

图 3 明文信号M(t)的轨迹

Figure 3. Trajectories of plaintext signal M(t)

下载: 全尺寸图片幻灯片

图 4 加密信号J(t)的轨迹

Figure 4. The trajectories of encrypted signal J(t)

下载: 全尺寸图片幻灯片

图 5 解密信号R(t)的轨迹

Figure 5. The trajectories of decrypted signal R(t)

下载: 全尺寸图片幻灯片

图 6 解密误差H(t)的轨迹

Figure 6. The trajectories of decryption error H(t)

下载: 全尺寸图片幻灯片

表 1 与其他文献控制器得到的调整时间对比

Table 1. Comparison of settling times obtained with other literature controllers

	controller	T_f
ref. [17]	u_i(t)=－ζ_1ie_i(t)－sign(e_i(t))(ζ_2i+ζ_3i\|e_i(t)\|^d₁+ζ_4i\|e_i(t)\|^d₂)	0.71
ref. [24]	u_i(t)=－ζ_2isign(e_i(t))－ζ_4isign(e_i(t))\|e_i(t)\|^d₂	1.81
ref. [25]	u_i(t)=－ζ_1ie_i(t)－sign(e_i(t))(ζ_2i+ζ_4i\|e_i(t)\|^d₂)	0.94
this paper	$ \boldsymbol{u}_{i}(t)=-\zeta_{1 i} \boldsymbol{e}_{i}(t)-\operatorname{sign}\left(\boldsymbol{e}_{i}(t)\right)\left(\zeta_{2 i}+\zeta_{3 i}\left\|\boldsymbol{e}_{i}(t)\right\|^{d_{1}}+\zeta_{4 i}\left\|\boldsymbol{e}_{i}(t)\right\|^{d_{2}}+\sum\limits_{i=1}^{n} \zeta_{5 i}\left\|\boldsymbol{e}_{j}(t-\mu(t))\right\|\right)$	0.65

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