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神经网络的规定的时间/固定时间/有限时间随机同步控制的新框架及其在图像加密中的应用

Xin Wang¹, Jinde Cao², Xianghui Zhou³

¹School of Computer Science and Technology, Huaiyin Normal University, Huaian 223300, Jiangsu, China; Huai'an Key Laboratory of Big Data Intelligent Computing and Analysis, Huaiyin Normal University, Huaian 223300, Jiangsu, China.

Neural networks : the official journal of the International Neural Network Society

|July 7, 2023

概括

本研究引入了一种用于半马尔科夫交换四次数值神经网络的新型控制框架,可实现规定的时间 (PAT),固定的时间 (FXT) 和有限时间 (FNT) 随机同步,具有预先分配的设置时间和有限的控制收益.

科学领域:

控制理论控制理论
人工智能的人工智能
神经网络的神经网络的神经网络

背景情况:

在半马尔科夫交换四次数值神经网络 (SMS-QVNNs) 中的随机同步对于复杂系统至关重要.
现有的规定时间 (PAT),固定时间 (FXT) 和有限时间 (FNT) 控制方法往往具有局限性,例如依赖其他控制类型或无限制的控制收益.

研究的目的:

为PAT,FXT和FNT开发一种新的,统一的框架,用于SMS-QVNNs的随机同步控制.
确保设置时间预先分配和估计.
克服现有控制框架的局限性,特别是控制收益的局限性.

主要方法:

提出了一个新的控制策略,集成了PAT,FXT和FNT的控制能力.
该框架确保有界的控制收益,即使时间接近规定的时间T.
通过数值模拟和图像加密/解密应用程序来证明有效性.

主要成果:

拟议的框架成功实现了PAT,FXT和FNT对SMS-QVNNs的随机同步.
同步的设置时间是有效地预先分配和估计的.
在整个同步过程中,控制收益仍然受到限制,与之前的一些方法不同.

结论:

这种新型框架为SMS-QVNNs的随机同步控制提供了强大而高效的解决方案.
这种方法提供了更大的灵活性和可靠性,通过统一不同的基于时间的控制策略与有限的收益.
展示的应用突显了拟议的控制策略的实际可行性.

关键词:

控制收益控制收益控制收益我们的框架框架框架.图像加密/解密的方法在 PAT/FXT/FNT 随机同步控制中使用 PAT/FXT/FNT.简短短信-QVNNs是什么意思

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