马尔科夫跳跃神经网络通过滑动模式控制的动态事件触发同步
IEEE transactions on cybernetics
|August 8, 2023
概括
这项研究引入了一种新的异步,动态事件触发滑动模式控制,用于马尔科夫跳跃神经网络. 该方法确保系统高效同步,只在必要时发送控制信号.
科学领域:
- 控制理论 控制理论
- 人工智能的人工智能
- 网络系统 网络系统
背景情况:
- 同步对于马尔科夫跳跃神经网络至关重要.
- 由于持续的信号传输,现有的控制方法可能效率低下.
研究的目的:
- 开发一个高效的异步和动态基于事件的滑动模式控制策略.
- 为了解决马尔科夫跳跃神经网络中的同步问题.
主要方法:
- 一个动态事件触发的方案,具有适应性定律和触发值.
- 设计一个具有增强不确定性的异步滑动模式控制器.
- 使用线性矩阵不等式来实现同步条件.
主要成果:
- 建立了足够的条件来保证系统同步.
- 控制器有效地将错误系统轨迹推向滑动表面.
- 建议的控制策略通过一个说明性的例子来验证.
结论:
- 基于事件的异步和动态滑动模式控制策略对于同步马尔科夫跳跃神经网络是有效的.
- 事件触发方法减少了控制信号的传输,提高了效率.
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