信号的语义刻画与度量

石光明; 高大化; 杨旻曦; 谢雪梅; 董明皓; 李雷达; 于凯

doi:10.12263/DZXB.20210238

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信号的语义刻画与度量

学术论文 | 更新时间：2025-12-08

- 信号的语义刻画与度量
- Semantic Characterization and Measurement of Signals
- 电子学报 2022年50卷第9期页码：2068-2078
- 作者机构：
  
  1.西安电子科技大学人工智能学院, 陕西西安 710071
  2.鹏城实验室,广东深圳 518055
  3.西安电子科技大学生命科学技术学院, 陕西西安 710071
- 作者简介：
  
  [ "石光明　男， 1965年06月出生于江西省南昌市. 长江学者特聘教授， IEEE Fellow， IET Fellow. 现任西安电子科技大学人工智能学院教授. 主要研究方向为人工智能、语义通信.E-mail: gmshi@xidian.edu.cn" ]
  [ "高大化　男， 1979年08月出生于河南省开封市. 现任西安电子科技大学人工智能学院教授. 主要研究方向为智能信息处理、智能感知. E-mail: dhgao@xidian.edu.cn" ]
  [ "杨旻曦　男， 1996年10月出生于四川省成都市. 现为西安电子科技大学人工智能学院博士研究生. 主要研究方向为表征学习、语义通信.E-mail: mxyang@stu.xidian.edu.cn" ]
  [ "谢雪梅　女， 1967年01月出生于陕西省西安市. 现任西安电子科技大学人工智能学院教授. 主要研究方向为场景理解与视频分析、多模态融合." ]
  [ "董明皓　男， 1984年05月出生于陕西省西安市. 现为西安电子科技大学分子与神经影像教育部工程研究中心副教授. 主要研究方向为脑机混合智能、人体效能增强.E-mail: dminghao@xidian.edu.cn" ]
  [ "李雷达　男， 1982年10月出生于江苏省徐州市. 现任西安电子科技大学人工智能学院教授. 主要研究方向为图像感知质量评价.E-mail: ldli@xidian.edu.cn" ]
  [ "于凯　男，1996年11月出生于山东省日照市莒县. 2018至2021年于西安电子科技大学人工智能学院攻读硕士学位. 主要研究方向为图像识别、增量学习.E-mail: yukai_nathan@163.com" ]
- 基金信息：
  
  国家重点研发计划课题(2019YFA0706604);国家自然科学基金(61871304;61976169;61875157);鹏城实验室重大攻关项目(PCL2021A12)
- DOI：10.12263/DZXB.20210238
  中图分类号： TP391.4
- 收稿：2021-02-09，
  
  修回：2022-02-02，
  
  纸质出版：2022-09-25
- 稿件说明：
移动端阅览
石光明,高大化,杨旻曦等.信号的语义刻画与度量[J].电子学报,2022,50(09):2068-2078.

SHI Guang-ming,GAO Da-hua,YANG Min-xi,et al.Semantic Characterization and Measurement of Signals[J].ACTA ELECTRONICA SINICA,2022,50(09):2068-2078.
石光明,高大化,杨旻曦等.信号的语义刻画与度量[J].电子学报,2022,50(09):2068-2078. DOI： 10.12263/DZXB.20210238.

SHI Guang-ming,GAO Da-hua,YANG Min-xi,et al.Semantic Characterization and Measurement of Signals[J].ACTA ELECTRONICA SINICA,2022,50(09):2068-2078. DOI： 10.12263/DZXB.20210238.

摘要

相比于基于比特数据的信息处理及通信技术，人类通过语义处理和传递信息的方式，在面对智能体间传递处理海量信息这一问题时显得更为高效和自然.然而由于目前缺乏关于语义度量和刻画的数学描述，涉及语义的应用无法兼顾可解释性和泛化性，无法发挥语义的高效自然的优势.本文围绕语义的度量和刻画，首先依据信息科学和神经科学相关结论，讨论了语义的内涵，并指出语义具有模块化、多模态、层级化的特点；接着提出了一种多模态信号的语义刻画和度量的数学描述；然后为了验证所提信号语义的刻画和度量的可行性和有效性，在MNIST（Mixed National Institute of Standards and Technology database）手写数字识别和水声目标识别两个应用中进行了实验，获得比传统深度学习更好的性能；最后将语义用于视频编码，实现了远超传统方法的压缩比，展现了语义在通信领域的实用价值.这为未来建立以语义为基础的新型信息处理与通信技术奠定了理论和实践基础.

Abstract

Compared with the modern information processing and communication technology based on bits

the semantic-based way of processing and transmitting information used by humans is more efficient and natural in the face of the massive information that needs to be sent between agents. However

due to the lack of mathematical description of semantic measurement and characterization

semantics' applications cannot consider both interpretability and generalization. Therefore

they cannot give play to the advantages of efficient and natural semantics. This paper focuses on the measurement and characterization of semantics. Firstly

we discuss the connotation of semantics based on the relevant conclusions of information science and neuroscience

and concludes that semantics has the characteristics of modularity

multi-mode

and hierarchy. Then

a semantic description of multimodal signals and a mathematical description of their measurement are proposed. Next

to verify the feasibility and effectiveness of the characterization and measurement of the proposed signal semantics

experiments are carried out in two applications: MNIST (Mixed National Institute of Standards and Technology database) handwritten digital recognition and underwater acoustic target recognition

and the results are better than those of the traditional deep learning. Finally

the semantics is used for video coding

and a compression ratio far exceeding that of traditional methods is achieved. This lays a theoretical and practical foundation for establishing new information processing and communication technology based on semantics.

关键词

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