Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Cui Minglei"'
Publikováno v:
In Bioresource Technology October 2022 361
Autor:
Hoover, Alicia 1, Sun, Dajun 2, Wen, Hong 2, Jiang, Wenlei 2, Cui, Minglei 2, Jiang, Xiaojian 2, Keire, David 1, Guo, Changning 1, ∗
Publikováno v:
In Journal of Pharmaceutical Sciences July 2017 106(7):1859-1864
Publikováno v:
In Pain 2004 107(1):125-133
Autor:
Cui, Minglei
This document only includes an excerpt of the corresponding thesis or dissertation. To request a digital scan of the full text, please contact the Ruth Lilly Medical Library's Interlibrary Loan Department (rlmlill@iu.edu).
Externí odkaz:
https://hdl.handle.net/1805/33643
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9783319089904
To solve the numerical instability in the recursive process of unscented Kalman filter (UKF), as well as the unsatisfactory performance in case of abrupt changes, a new adaptive target tracking method, called square root unscented Kalman filter based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::21233d9cac9f8c6ee2e12cb7977ef811
https://doi.org/10.1007/978-3-319-08991-1_83
https://doi.org/10.1007/978-3-319-08991-1_83
Publikováno v:
CIT
A new manifold learning algorithm, called robust kernel neighborhood preserving projection (RKNPP), is presented and applied to radar target recognition based on high resolution range profiles. RKNPP attempts to map the high-dimensional data into suc
Publikováno v:
IEEE 2011 10th International Conference on Electronic Measurement & Instruments.
A radar high resolution range profile (HRRP) contains rather detailed structural information of a target and provides us a more reliable tool for target recognition. Various feature extraction methods have been developed and applied to radar target r
Publikováno v:
2010 International Symposium on Intelligent Signal Processing and Communication Systems.
Recently, the computer vision and pattern recognition community has witnessed the rapid growth of a new kind of dimensionality reduction method, namely manifold learning. Among them, neighborhood preserving embedding (NPE) is one of the most promisin
Publikováno v:
2012 IEEE 12th International Conference on Computer & Information Technology; 1/ 1/2012, p809-813, 5p