Principal component analysis is a versatile tool to reduce dimensionality which has wide applications in statistics and machine learning. It is particularly useful for modeling data in high-dimensi…
Functional data analysis has attracted considerable interest and is facing new challenges, one of which is the increasingly available data in a streaming manner. In this article we develop an onlin…
For spatially dependent functional data, a generalized Karhunen-Loève expansion is commonly used to decompose data into an additive form of temporal components and spatially correlated coefficient…
This paper concerns upper estimates of the projectional coderivative of implicit mappings and corresponding applications on analyzing the relative Lipschitz-like property. Under different constrain…
In multiple change-point analysis, one of the main difficulties is to determine the number of change-points. Various consistent selection methods, including the use of Schwarz information criterion…
An all-single-mode fiber intracavity displacement sensor based on U-shaped single-mode fiber interferometer (U-SMFI) is demonstrated theoretically and experimentally. The theoretical model for a ca…
In this article, a long-wave infrared InAs/GaAs sub-monolayer quantum dot quantum cascade photodetector (SML QD-QCD) grown on GaAs substrate is demonstrated. Temperature- and excitation-dependent p…