参数不匹配的延迟随机四元数值模糊蜂窝神经网络的准投影同步控制

IF 4.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xiaofang Meng, Yu Fei, Zhouhong Li
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引用次数: 0

摘要

本文讨论了参数不匹配的延迟随机四元模糊蜂窝神经网络的准投影同步问题。虽然驱动-响应系统的参数不匹配增加了文章的计算复杂度,但考虑两个系统之间存在偏差具有实际意义。本文的方法是设计一个合适的控制器,并基于四元数域中的 Itô 公式构建 Lyapunov 函数和随机分析理论。我们采用了四元数 FCNN 的不可分解方法,既保留了原始数据,又减少了计算量。我们获得了参数不匹配的随机四元数 FCNN 准投影同步的充分条件。此外,我们还估算了准投影同步的误差边界,并通过一个数值示例验证了其有效性。即使所考虑的神经网络退化为实值或复值神经网络,我们的结果也是新颖的。本文为研究带时延的随机四元数值 FCNN 的准投影同步问题提供了一个很好的研究思路,并取得了很好的效果。本文的方法也可用于研究 Clifford 值神经网络的准投影同步问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Quasi-projective Synchronization Control of Delayed Stochastic Quaternion-Valued Fuzzy Cellular Neural Networks with Mismatched Parameters

Quasi-projective Synchronization Control of Delayed Stochastic Quaternion-Valued Fuzzy Cellular Neural Networks with Mismatched Parameters

This paper deals with the quasi-projective synchronization problem of delayed stochastic quaternion fuzzy cellular neural networks with mismatch parameters. Although the parameter mismatch of the drive-response system increases the computational complexity of the article, it is of practical significance to consider the existence of deviations between the two systems. The method of this article is to design an appropriate controller and construct Lyapunov functional and stochastic analysis theory based on the Itô formula in the quaternion domain. We adopt the non-decomposable method of quaternion FCNN, which preserves the original data and reduces computational effort. We obtain sufficient conditions for quasi-projective synchronization of the considered random quaternion numerical FCNNs with mismatched parameters. Additionally, we estimate the error bounds of quasi-projective synchronization and then carry out a numerical example to verify their validity. Our results are novel even if the considered neural networks degenerate into real-valued or complex-valued neural networks. This article provides a good research idea for studying the quasi-projective synchronization problem of random quaternion numerical FCNN with time delay and has obtained good results. The method in this article can also be used to study the quasi-projective synchronization of a Clifford-valued neural network.

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来源期刊
Cognitive Computation
Cognitive Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-NEUROSCIENCES
CiteScore
9.30
自引率
3.70%
发文量
116
审稿时长
>12 weeks
期刊介绍: Cognitive Computation is an international, peer-reviewed, interdisciplinary journal that publishes cutting-edge articles describing original basic and applied work involving biologically-inspired computational accounts of all aspects of natural and artificial cognitive systems. It provides a new platform for the dissemination of research, current practices and future trends in the emerging discipline of cognitive computation that bridges the gap between life sciences, social sciences, engineering, physical and mathematical sciences, and humanities.
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