分散网络转变度:用于描述非线性信号复杂性的度量
Bo Geng1,2, Haiyan Wang1,3, Xiaohong Shen1,2
1School of Marine Science and Technology, <a href="https://ror.org/01y0j0j86">Northwestern Polytechnical University</a>, Xi'an, Shaanxi 710072, China.
一个新的信号复杂度度指标,分散网络过渡 (DNTE),准确量化非线性信号动态. 对于分析诸如水下声学之类的复杂信号,DNTE的准确性和效率优于现有的方法.
科学领域:
- 信号处理 信号处理
- 复杂系统分析 复杂系统分析
- 信息理论 信息理论
背景情况:
- 从噪音,非线性信号中提取信息是一项挑战.
- 传统的指标与动态特性和复杂的信号结构作斗争.
- 环境噪声往往会在收集的信号中引入非线性.
研究的目的:
- 提出一种创新的度量,分散网络转变 (DNTE),用于量化信号复杂性.
- 解决传统指标在分析非线性信号方面的局限性.
- 开发一种集成复杂网络和信息的方法,用于信号分析.
主要方法:
- 使用累积分布函数和马尔科夫链,将非线性信号转换为加权定向复杂网络.
- 评估网络节点和链接的重要性.
- 使用信息来量化信号复杂性的DNTE计算.
主要成果:
- DNTE准确地反映了信号复杂性的变化.
- 与Lempel-Ziv复杂度,变和分散相比,DNTE显示出更高的计算效率.
- DNTE擅长区分混乱的模型,船只和调制信号.
结论:
- DNTE是一种强大的新指标,用于量化信号复杂度.
- 对于非线性信号分析,DNTE在准确性和效率方面提供了卓越的性能.
- DNTE显示出从多种信号中有效提取信息的巨大潜力.
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