Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Hong-Fan Zhang"'
Publikováno v:
Sensors, Vol 23, Iss 7, p 3495 (2023)
It is critical to accurately align a quantum photon detector such as a superconducting transition-edge sensor (TES) to an optical fiber in order to optimize its detection efficiency. Conventionally, such alignment requires advanced infrared imaging e
Externí odkaz:
https://doaj.org/article/a9a682ec388548e19c7a0290fe0e907a
Publikováno v:
Computational Statistics & Data Analysis. 141:28-39
This paper concerns the bootstrap consistency of the minimum average variance estimation (MAVE) method for the single index model. This paper shows that the conditional wild bootstrap estimator of the parameter index shares the same asymptotic covari
Publikováno v:
Optics Express. 31:737
Conventional methods have relied on specialized imaging equipment and advanced fabrication process to solve the problem of accurately aligning a microsensor to an optical fiber which is critical for its detection efficiency. To dramatically lower the
Publikováno v:
Open Mathematics, Vol 16, Iss 1, Pp 986-998 (2018)
Stochastic Automata Networks (SANs) have a large amount of applications in modelling queueing systems and communication systems. To find the steady state probability distribution of the SANs, it often needs to solve linear systems which involve their
Autor:
Hong-Fan Zhang
Publikováno v:
Journal of Multivariate Analysis. 184:104753
The Minimum Average Variance Estimation (MAVE) method and its variants have proven to be effective approaches to the dimension reduction problems. However, as far as we know, using MAVE to estimate the Central Mean Subspace (CMS) with multivariate re
Autor:
Hong-Fan Zhang
Publikováno v:
Computational Statistics & Data Analysis. 156:107145
In this paper, we consider the estimation method for the partially linear single-index model with endogenous regressors in the linear part. The Generalized Method of Moments (GMM) using instrumental variables is applied to cope with the problem that
Publikováno v:
Journal of Computational and Applied Mathematics. 296:397-409
This paper formulates the PageRank problem A x = x into a consistent singular linear system ( I - A ) x = 0 , and applies the full orthogonalization method (FOM) to solve it. This singular system is characterized by index one, namely i n d e x ( I -
Publikováno v:
Proceedings of the 5th International Conference on Bioinformatics and Computational Biology.
This paper proposes an aggregation multigrid method for computing the GeneRank problem. In this multigrid, the GeneRank transition matrix's formulation is well exploited, and a Block-Jacobi relaxation based on the aggregates, is employed. This block