Classifying emitters in the high frequency range with self-organizing maps

被引：0

作者：

Fanghänel, K ^{[1
]}

Köllmann, K ^{[1
]}

Raps, F ^{[1
]}

Zeidler, HC ^{[1
]}

机构：

[1] Univ Bundeswehr Hamburg, Holstenhofweg 85, D-22043 Hamburg, Germany

来源：

IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL VI | 2000年

关键词：

D O I：

10.1109/IJCNN.2000.859407

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper Self-Organizing Maps (SOMs) are proposed for classifying emitters in the high frequency range allowing verification of emitters received by dislocated sensors. With respect to the characteristics of SOMs the classification and verification can be done without any model based knowledge of the different transmission channels. Moreover, both processes seem to be robust against data losses based on a discrete wavelet transform.

引用

页码：265 / 269

页数：5

共 50 条

[1] Classifying news corpus by self-organizing maps
Yanagida, T
Miura, T
Shioya, I
2003 IEEE PACIFIC RIM CONFERENCE ON COMMUNICATIONS, COMPUTERS, AND SIGNAL PROCESSING, VOLS 1 AND 2, CONFERENCE PROCEEDINGS, 2003, : 800 - 803
[2] An essay in classifying Self-organizing Maps for temporal sequence processing
Guimaraes, G
Moura-Pires, F
ADVANCES IN SELF-ORGANISING MAPS, 2001, : 259 - 266
[3] Self-Organizing Maps
Matera, F
SUBSTANCE USE & MISUSE, 1998, 33 (02) : 365 - 381
[4] Classifying gamma-ray bursts using self-organizing maps
Rajaniemi, HJ
Mähönen, P
ASTROPHYSICAL JOURNAL, 2002, 566 (01): : 202 - 209
[5] Self-Organizing Maps in High Energy Physics
Habermann, Kai
von Toerne, Eckhard
20TH INTERNATIONAL WORKSHOP ON ADVANCED COMPUTING AND ANALYSIS TECHNIQUES IN PHYSICS RESEARCH, 2023, 2438
[6] SOM of SOMs: Self-organizing map which maps a group of self-organizing maps
Furukawa, T
ARTIFICIAL NEURAL NETWORKS: BIOLOGICAL INSPIRATIONS - ICANN 2005, PT 1, PROCEEDINGS, 2005, 3696 : 391 - 396
[7] A dimension range representation (DRR) measure for self-organizing maps
Clark, Stephanie
Sisson, Scott. A.
Sharma, Ashish
PATTERN RECOGNITION, 2016, 53 : 276 - 286
[8] A Rapid Technique for Classifying Phytoplankton Fluorescence Spectra Based on Self-Organizing Maps
Aymerich, Ismael F.
Piera, Jaume
Soria-Frisch, Aureli
Cros, Lluisa
APPLIED SPECTROSCOPY, 2009, 63 (06) : 716 - 726
[9] Wavelet-based self-organizing maps for classifying multivariate time series
D'Urso, Pierpaolo
De Giovanni, Livia
Maharaj, Elizabeth Ann
Massari, Riccardo
JOURNAL OF CHEMOMETRICS, 2014, 28 (01) : 28 - 51
[10] THE SELF-ORGANIZING FEATURE MAPS
KOHONEN, T
MAKISARA, K
PHYSICA SCRIPTA, 1989, 39 (01): : 168 - 172

← 1 2 3 4 5 →