Zobrazeno 1 - 10
of 91
pro vyhledávání: '"Ying-Ke Lei"'
Publikováno v:
Symmetry, Vol 13, Iss 7, p 1215 (2021)
Specific emitter identification involves extracting the fingerprint features that represent the individual differences of the emitter through processing the received signals. By identifying the extracted fingerprint features, one can also identify th
Externí odkaz:
https://doaj.org/article/c4cbd338ffda400eb3f6144a5f543440
Autor:
Zhe TANG, Ying-ke LEI
Publikováno v:
Tongxin xuebao, Vol 37, Pp 171-175 (2016)
To measure the similarity between the fine features of communication transmitters, a method of individual communication transmitter identification based on maximum correntropy was put forward. Firstly, the square integral bispectra was extracted to c
Externí odkaz:
https://doaj.org/article/5da526866af749bea90022d2e769af6d
Publikováno v:
Communications in Theoretical Physics. 74:115201
In Asakaet al(2021Phys. Rev. D103, 015014), Asaka, Ishida and Tanaka put forward an interesting possibility that the neutrinoless double beta decay can be hidden in the minimal seesaw model with the two right-handed neutrinos having a hierarchical ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc201d5bf48c5f45e5715f61ac7ea3d2
https://doi.org/10.1088/1572-9494/ac85a6
https://doi.org/10.1088/1572-9494/ac85a6
Autor:
Ying-ke Lei, Jian-hang Huang
Publikováno v:
Wireless Personal Communications. 103:2729-2742
Aiming at the difficulty of extracting radio fingerprint feature caused by insufficient traditional training method under small labeled sample prerequisite, the deep autoencoders regularized by marginal Fisher analysis algorithm for radio fingerprint
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d43e650f3217e4f2b9a39c348cacf8b1
https://doi.org/10.1007/s11277-018-5958-0
https://doi.org/10.1007/s11277-018-5958-0
Autor:
Xin Li, Ying-ke Lei
Publikováno v:
2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC).
Due to the small sample of communication station signals and the weak fingerprint characteristics of radio stations, the accuracy of individual identification of communication stations is not high. This paper firstly proposes the identification of co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8778e01874132f78421c2842610ff481
https://doi.org/10.1109/itaic.2019.8785501
https://doi.org/10.1109/itaic.2019.8785501
Publikováno v:
Modern Physics Letters A. 35:2050218
A machine learning method is applied to analyze lepton mass matrices numerically. The matrices were obtained within a framework of high-scale supersymmetry (SUSY) and a flavor symmetry, which are too complicated to be solved analytically. In this num
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ab4269d5df591df021e9adff6ce544c
https://doi.org/10.1142/s0217732320502181
https://doi.org/10.1142/s0217732320502181
Publikováno v:
DEStech Transactions on Computer Science and Engineering.
Aiming at Finite set identification problem of the channel encoding of LDPC code identification system, a novel coding identification algorithm for LDPC Codes using Soft decision sequence is proposed in this paper. The algorithm will introduce the re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::164f92d6e3835bb3d00f18860ec193fa
https://doi.org/10.12783/dtcse/cnai2018/24156
https://doi.org/10.12783/dtcse/cnai2018/24156
Publikováno v:
Knowledge-Based Systems. 89:47-55
In this paper, an efficient feature extraction algorithm called discriminant sparse local spline embedding (D-SLSE) is proposed for face recognition. A sparse neighborhood graph of the input data is firstly constructed based on a sparse representatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::34d22ba57aa26637fcae2e9f393f6b37
https://doi.org/10.1016/j.knosys.2015.06.016
https://doi.org/10.1016/j.knosys.2015.06.016
Publikováno v:
Pattern Analysis and Applications. 19:953-961
Plant classification based on the leaf images is an important and tough task. For leaf classification problem, in this paper, a new weight measure is presented, and then a dimensional reduction algorithm, named semi-supervised orthogonal discriminant
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3aae3e3366a93f1f3a63284169af43cf
https://doi.org/10.1007/s10044-015-0488-9
https://doi.org/10.1007/s10044-015-0488-9
Publikováno v:
Soft Computing. 20:263-271
An important application of gene expression data is tumor classification. Dimensionality reduction is a key step of tumor classification as gene expression data have the so-called large and small problem. To reduce the dimensionality of the microarra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60a7f4f7a10f8a5fa272e01a65787e70
https://doi.org/10.1007/s00500-014-1501-8
https://doi.org/10.1007/s00500-014-1501-8