V
主页
【测度概率论】MTP lecture 10-1
发布人
Discuss the measure- and Lebesgue integration theory that is relevant in probability theory. Introduce some vital concepts in probability theory, such as conditional expectations, the Radon-Nikodym theorem, martingale convergence theorems, characteristic functions and why they are characteristic, the Brownian motion. Provide rigorous proofs for two central convergence theorems in probability: the Strong Law of Large Numbers and the Central Limit Theorem.
打开封面
下载高清视频
观看高清视频
视频下载器
【测度概率论】MTP lecture 9-1
【测度概率论】MTP lecture 7-2
【测度概率论】MTP lecture 8-2
【测度概率论】MTP lecture 13-1
【测度概率论】MTP lecture 6-1
【测度概率论】MTP lecture 9-2
【测度概率论】MTP lecture 4-1
【测度概率论】MTP lecture 13-2
【测度概率论】MTP lecture 5-1
【测度论进阶课 IMPA】
【概率论进阶课 IMPA】
MTP lecture 5 - remark - 1080p
测度与积分,第九讲(Measures and Integrals, 9th Class, 2022)
lecture_10_(2_2)_category_theory_(2022) (1080p)
【随机积分】11
lecture_10_(2_2)_ergodic_theory_(2022) (1080p)
lecture_11_(1_2)_category_theory_(2022) (1080p)
lecture_12_(2_2)_category_theory_(2022) (1080p)
【随机积分】7.1
【随机积分】9.1
【随机积分】9.3
lecture_12_(2_2)_ergodic_theory_(2022) (1080p)
【随机积分】8.1
lecture_3_(1_2)_ergodic_theory_(2022) (1080p)
lecture_2_(2_2)_ergodic_theory_(2022) (1080p)
3.5-1二维随机变量函数的分布
lecture_4_(2_2)_category_theory_(2022) (1080p)
lecture_3_(2_2)_category_theory_(2022) (1080p)
lecture_9_(2_2)_category_theory_(2022) (1080p)
lecture_6_(2_2)_ergodic_theory_(2022) (1080p)
lecture_7_(1_2)_ergodic_theory_(2022) (1080p) (1)
lecture_5_(1_2)_ergodic_theory_(2022) (1080p)
lecture_8_(1_2)_category_theory_(2022) (1080p)
lecture_14_(2_2)_ergodic_theory_(2022) (1080p)
【微分几何】10-3
lecture_10_(1_2)_ergodic_theory_(2022) (1080p)
【随机积分】9.2
【随机积分】7.4
lecture_5_(2_2)_ergodic_theory_(2022) (1080p)
【微分几何】15-1