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Beijing Institute of Technology

Information Theory

Beijing Institute of Technology via XuetangX

Overview

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由北京理工大学牵头建设的《Information Theory(信息论)》慕课,特邀了知名专家叶建宏教授建设并录制了这门课。相信这门课可以帮助大学生朋友们掌握信息论,及这些理论在相关专业应用方法和技术,为未来的科研与工程应用奠定良好基础。

 

这门慕课课程有三个突出的特色:

首先,理论与实践紧密结合。基于香农信息论,揭示信息本质及内涵,围绕信源和信道,探索如何实现信息有效、可靠地传输。这种理论与实践的结合不仅能够帮助学习者理解信息论的基本原理,还能够让他们看到这些理论在实际系统中的应用,从而加深对信息论重要性的认识。

第二,跨学科的知识融合。内容涵盖了信息论基本原理、信息论测度、信道容量、编码技术等方面的知识。这些内容不仅涉及信息论本身,还与概率论、随机过程、信号处理、密码学等多个学科领域交叉。学习者通过课程学习,能够掌握跨学科知识,这对于学生在未来学术或职业生涯中解决复杂问题具有重要价值。

第三,实际应用案例分析:通过实际案例分析,使学习者能够直观地看到信息论理论在解决实际问题中的作用。课程旨在增强学习者将理论知识应用于实践能力,为他们将来在各自领域中应用信息论打下坚实基础。



Syllabus

  • 01 An Overview of Information Theory
    • 1.1 Introduction to Information Theroy
    • 1.2 Main Research Content of Information Theory
    • 1.3 Development and Application of Information Theory
    • 1.4 Exercises
  • 02 Source Model
    • 2.1 Source Model
    • 2.2 Self-Information
    • 2.3 Definition of Shannon Entropy
    • 2.4 Properties of Entropy
    • 2.5 Joint/Conditional Self-Information
    • 2.6 Mutual Information and Properties
    • 2.7 Extended Discrete Memoryless Sources
    • 2.8 Entropy of Discrete Memory Sources
    • 2.9 Entropy Rate of Markov Chains
    • 2.10 Entropy Rate of Discrete Sources and Information Efficiency
    • 2.11 Differential Entropy of Continuous Random Variables and Mutual Information
    • 2.12 Exercises
  • 03 Channels and Channel Capacity
    • 3.1 Channel Model and Classification
    • 3.2 Mathematical Model of DMC
    • 3.3 Probability Calculation of DMC
    • 3.4 Doubtful Measure, Dispersion Measure, and Average Mutual Information
    • 3.5 Channel Capacity
    • 3.6 Extended Channel and Its Capacity
    • 3.7 Channel Combinations
    • 3.8 Source-Channel Matching
    • 3.9 Continuous Channel and Its Channel Capacity
    • 3.10 Waveform Channel and Its Channel Capacity
    • 3.11 Exercises
  • 04 Information Theory and Coding
    • 4.1 Introduction to Source Coding
    • 4.2 Uniquely Decodable Code
    • 4.3 Fixed-Length Coding Theorem and Methods
    • 4.4 Variable-Length Source Coding Theorem
    • 4.5 Variable-Length Codes
    • 4.6 Exercises
  • Final examination

    Taught by

    Chien-Hung Yeh and Wenbin Shi

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