Results 11 to 20 of about 830,323 (220)

Model-Based Fuzzy $l_{2}-l_{\infty }$ Filtering for Discrete-Time Semi-Markov Jump Nonlinear Systems Using Semi-Markov Kernel

IEEE Transactions on Fuzzy Systems, 2022
This article concentrates on the model-based fuzzy $l_{2}-l_{\infty }$ filtering problem of a discrete-time semi-Markov jump nonlinear system. The random jumps in the studied system are governed by the discrete-time semi-Markov process.
Jing Wang, Yigang Zhang, Lei Su, Ju H. Park, Hao Shen   +4 more
semanticscholar   +3 more sources

Quantum tomography, phase space observables, and generalized Markov kernels [PDF]

Journal of Physics A: Mathematical and Theoretical, 2009
We construct a generalized Markov kernel which transforms the observable associated with the homodyne tomography into a covariant phase space observable with a regular kernel state.
Abramowitz M, Albini P, Ali S T, Butzer P L, Epstein C L, Helgason S, Ibort A, Juha-Pekka Pellonpää, Kiukas J, Kiukas J Werner R, Leonhardt U, Pandey J N, Pellonpää J-P, Reed M, Riordan J, Spanier J   +15 more
core   +2 more sources

Rate Functions for Symmetric Markov Processes via Heat Kernel [PDF]

Potential Analysis, 2015
By making full use of heat kernel estimates, we establish the integral tests on the zero-one laws of upper and lower bounds for the sample path ranges of symmetric Markov processes.
Yuichi Shiozawa, Jian Wang
semanticscholar   +4 more sources

Blind Super-Resolution via Meta-Learning and Markov Chain Monte Carlo Simulation [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning based approaches have witnessed great successes in blind single image super-resolution (SISR) tasks, however, handcrafted kernel priors and learning based kernel priors are typically required. In this paper, we propose a meta-learning and Markov
Jingyuan Xia, Zhixiong Yang, Shengxi Li, Shuanghui Zhang, Yaowen Fu, Deniz Gündüz, Xiang Li   +6 more
semanticscholar   +3 more sources

Kernel-based Hidden Markov Conditional Densities

SSRN Electronic Journal, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jan G. De Gooijer, Gustav Eje Henter, Ao Yuan   +2 more
openaire   +4 more sources

Transportation inequalities for Markov kernels and their applications [PDF]

Electronic Journal of Probability, 2021
38 pages.
Baudoin, Fabrice, Eldredge, Nathaniel
openaire   +4 more sources

Maximal asymmetry of bivariate copulas and consequences to measures of dependence

Dependence Modeling, 2022
In this article, we focus on copulas underlying maximal non-exchangeable pairs (X,Y)\left(X,Y) of continuous random variables X,YX,Y either in the sense of the uniform metric d∞{d}_{\infty } or the conditioning-based metrics Dp{D}_{p}, and analyze their ...
Griessenberger Florian, Trutschnig Wolfgang   +1 more
doaj   +1 more source

Approximate Bayesian Computation for Discrete Spaces

Entropy, 2021
Many real-life processes are black-box problems, i.e., the internal workings are inaccessible or a closed-form mathematical expression of the likelihood function cannot be defined.
Ilze A. Auzina, Jakub M. Tomczak
doaj   +1 more source

A kernel mixing strategy for use in adaptive Markov chain Monte Carlo and stochastic optimization contexts

Frontiers in Applied Mathematics and Statistics, 2022
Performing Markov chain Monte Carlo parameter estimation on complex mathematical models can quickly lead to endless searching through highly multimodal parameter spaces.
Graham West, Zachariah Sinkala, John Wallin   +2 more
doaj   +1 more source

A link between Kendall’s τ, the length measure and the surface of bivariate copulas, and a consequence to copulas with self-similar support

Dependence Modeling, 2023
Working with shuffles, we establish a close link between Kendall’s τ\tau , the so-called length measure, and the surface area of bivariate copulas and derive some consequences.
Sánchez Juan Fernández, Trutschnig Wolfgang   +1 more
doaj   +1 more source