基于流式图形信号的可靠分布式估计的扩散策略
Xinyu Li1, Feng Chen2, Qing Shi2
1School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China.
ISA transactions
|June 22, 2023
概括
本研究介绍了一个扩散混合电流量 (d-MC) 算法,用于对动态图形信号进行强大的分布式估计. 新方法有效处理高斯式和冲动式噪声,优于现有的方法.
科学领域:
- 信号处理 信号处理
- 网络科学 网络科学
- 机器学习 机器学习
背景情况:
- 对动态图信号的分布式估计至关重要,但现有的方法在与非高斯噪声作斗争.
- 基于平均平方误差 (MSE) 的方法对冲动或非高斯干扰很敏感.
研究的目的:
- 为动态和流式图形信号开发一个强大的分布式估计算法.
- 解决现有方法在处理非高斯噪声环境中的局限性.
主要方法:
- 提出了一种新型的扩散混合电流 (d-MC) 算法.
- 该算法包含了一个扩散策略和一个新的成本函数,该函数基于混合曲率.
- 进行了平均值和平方平均值稳定性的理论分析.
主要成果:
- 拟议的d-MC算法从动态和流式图形信号中准确估计图形波器参数.
- 该算法在高斯和冲动噪声的存在下表现出强大的性能.
- 与基准方法相比,模拟证实了d-MC算法的优越性.
结论:
- 扩散混合电流量 (d-MC) 算法为动态图信号的分布式估计提供了一个强大的解决方案.
- d-MC算法有效地减轻了非高斯噪声的影响,提高了估计准确性和稳定性.
- 这项工作为噪音大,动态网络环境中的信号处理提供了宝贵的进步.
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