Generalized Mehler semigroups:: The non-Gaussian case

被引:50
|
作者
Fuhrman, M
Röckner, M
机构
[1] Politecn Milan, Dipartimento Matemat, I-20133 Milan, Italy
[2] Univ Bielefeld, Fak Math, D-33501 Bielefeld, Germany
关键词
Markovian semigroups; Mehler formula; cadlag processes in abstract spaces; tightness of capacities;
D O I
10.1023/A:1008644017078
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
We study generalized Mehler semigroups, introduced in [7], with special emphasis on the non-Gaussian case. We review and simplify the method of construction. In the general (non-Gaussian) case we construct an associated cadlag Markov process in an appropriate state space obtained as a solution of a stochastic equation which can be solved 'omega by omega'. We also show tightness of the associated (r, p)-capacities. Invariant measures, time regularity and a definition of the generator are also studied.
引用
收藏
页码:1 / 47
页数:47
相关论文
共 50 条
  • [41] Infinite-dimensional non-Gaussian analysis and generalized translation operators
    Berezansky, YM
    FUNCTIONAL ANALYSIS AND ITS APPLICATIONS, 1996, 30 (04) : 269 - 272
  • [42] Infinite dimensional non-Gaussian analysis connected with generalized translation operators
    Berezansky, YM
    ANALYSIS ON INFINITE-DIMENSIONAL LIE GROUPS AND ALGEBRAS, 1998, : 22 - 46
  • [43] A non-Gaussian Bayesian filter using power and generalized logarithmic moments
    Wu, Guangyu
    Lindquist, Anders
    AUTOMATICA, 2024, 166
  • [44] Generalized minimum error entropy Kalman filter for non-Gaussian noise
    He, Jiacheng
    Wang, Gang
    Yu, Huijun
    Liu, JunMing
    Peng, Bei
    ISA TRANSACTIONS, 2023, 136 : 663 - 675
  • [45] Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables
    Tenzer, Yaniv
    Soloveytchik, Ilya
    Wiesel, Ami
    Elidan, Gal
    ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 51, 2016, 51 : 222 - 230
  • [46] Non-Gaussian clutter modeling with generalized spherically invariant random vectors
    Barnard, TJ
    Weiner, DD
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1996, 44 (10) : 2384 - 2390
  • [47] Generalized Correntropy based deep learning in presence of non-Gaussian noises
    Chen, Liangjun
    Qu, Hua
    Zhao, Jihong
    NEUROCOMPUTING, 2018, 278 : 41 - 50
  • [48] STATISTICAL PERFORMANCE OF NON-GAUSSIAN ENVELOPE SIGNAL IN THE PRESENCE OF THE NON-GAUSSIAN INTERFERENCE
    AGAYEV, SK
    KARPOV, IG
    RUSINOV, VR
    IZVESTIYA VYSSHIKH UCHEBNYKH ZAVEDENII RADIOELEKTRONIKA, 1991, 34 (04): : 93 - 96
  • [49] Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data
    Zilber, Daniel
    Katzfuss, Matthias
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2021, 153
  • [50] Moments of non-Gaussian Wigner distributions and a generalized uncertainty principle: I. The single-mode case
    Ivan, J. Solomon
    Mukunda, N.
    Simon, R.
    JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2012, 45 (19)