- 广义概率论发展前景--关于趣味数学与置信函数实际应用的一些原创观点(英文)/国外优秀数学著作原版系列
- - 作者：(意)法比奥·库佐林|责编:张永芹//邵长玲
  - 出版社：哈尔滨工业大学
  - ISBN：9787576706772
  - 出版日期：2023/03/01
  - 页数：231
- 售价：19.2

内容大纲
本书共分为四个部分，第一部分介绍了相关概念；第二部分阐述并讨论了作为数学对象的信任函数的几何和代数性质的新奇的理论结果，重点是对不确定性的透视的“几何方法”和证据冲突的代数解的阐释；第三部分展示了这些理论是如何从重要的计算机视觉问题中产生并发展起来的（如对象跟踪、数据关联和物体定位），而证据形式主义又可以为这些问题提供有趣的、新的解决方案；最后一部分初步研究了将全概率的概念推广到信任函数的相关内容。
作者介绍
目录
Preface
  CHAPTER 1. Introduction
Part 1. Belief calculus
  CHAPTER 2. Shafer's mathematical theory of evidence
    1. Belief functions
    2. Dempster's rule of combination
    3. Simple and separable support functions
    4. Families of compatible frames of discernment
    5. Support functions
    6. Impact of the evidence
    7. Quasi support functions
    8. Consonant belief functions
  CHAPTER 3. State of the art
    1. The alternative interpretations of belief functions
    2. Frameworks and approaches
    3. Conditional belief functions
    4. Statistical inference and estimation
    5. Decision making
    6. Efficient implementation of belief calculus
    7. Continuous belief functions
    8. Other theoretical developments
    9. Relation with other mathematical theories of uncertainty
    10. Applications
Part 2. Advances
  CHAPTER 4. A geometric approach to belief calculus
    1. The space of belief functions
    2. Simplicial form of the belief space
    3. The bundle structure of the belief space
    4. Global geometry of Dempster's rule
    5. Pointwise geometry of Dempster's rule
    6. Applications of the geometric approach
    7. Conclusive comments
  CHAPTER 5. Algebraic structure of the families of compatible frames
    1. Axiom analysis
    2. Monoidal structure of families of frames
    3. Lattice structure of families of frames
    4. Semimodular structure of families of frames
  CHAPTER 6. Algebra of independence and conflict
    I. Independence of frames and Dempster's combination
    2. An algebraic study of independence of flames
    3. Independence on lattices versus independence of frames
    4. Perspectives
    5. Conclusive comments
Part 3. Visions
  CHAPTER 7. Data association and the total belief theorem
    1. The data association problem
    2. The total belief theorem
    3. The restricted total belief theorem
    4. Conclusive comments
  CHAPTER 8. Belief Modeling Regression

    1. Scenario
    2. Learning evidential models
    3. Regression
    4. Assessing evidential models
    5. Results on human pose estimation
    6. Discussion
    7. Towards evidential tracking
    8. Conclusive comments
Part 4. Conclusions
  CHAPTER 9. Conclusions
Bibliography
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