状态依赖的切换神经网络的固定/规定的时间同步,具有随机干扰和冲动效应
Guici Chen1, Houxuan Zhang2, Shiping Wen3
1Hubei Province Key Laboratory of System Science in Metallurgical Process, Wuhan University of Science and Technology, Wuhan, 430065, China; Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, 430074, China; College of Science, Wuhan University of Science and Technology, Wuhan, 430065, China.
概括
这项研究在状态依赖切换神经网络 (SDSNNs) 中实现了固定时间 (FXTS) 和规定的时间 (PSTS) 的同步,这些神经网络具有干扰和冲动. 一个新的PI控制框架确保了稳定性和性能,平衡同步与系统动态.
科学领域:
- 控制理论 控制理论
- 计算神经科学是一种神经科学.
- 非线性动力学是一种非线性动力学.
背景情况:
- 状态依赖切换神经网络 (SDSNNs) 是易受随机干扰和冲动效应的复杂系统.
- 在固定的或规定的时间框架内实现同步对于可靠的网络运行至关重要,但由于系统不确定性而具有挑战性.
研究的目的:
- 调查具有随机干扰和冲动效应的SDSNN的固定时间同步 (FXTS) 和规定的时间同步 (PSTS).
- 开发一个统一的控制框架,以实现强大的和高效的同步.
主要方法:
- 用间隔矩阵转换将随机扰动和冲动的SDSNN重制成间隔参数系统.
- 使用线性矩阵不等式 (LMIs) 来推导FXTS和PSTS的足够条件.
- 开发一个统一的比例积分 (PI) 控制框架,用于控制器设计.
主要成果:
- 在LMI的形式中,为FXTS和PSTS获得了足够的条件.
- 成功开发了一个统一的PI控制框架,以实现FXTS和PSTS.
- 提出的方法证明了通过参数配置来平衡同步性能的有效性.
结论:
- 该研究为复杂的SDSNNs中的FXTS和PSTS提供了一个新的分析框架.
- 统一的PI控制框架为管理冲动效应和实现所需的同步时间提供了强大的解决方案.
- 通过说明性示例验证了理论结果,证实了拟议方法的有效性.
相关概念视频
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