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Targeted radioligand therapy: physics and biology, internal dosimetry and other practical aspects during ¹⁷⁷Lu/²²⁵Ac treatment in neuroendocrine tumors and metastatic prostate cancer. [PDF]

Theranostics
Dadgar H, Pashazadeh A, Norouzbeigi N, Assadi M, Al-Balooshi B, Baum RP, Al-Ibraheem A, Haidar M, Beheshti M, Geramifar P, Vali R, Mohammadi S, Dash S, Malasani V, Cimini A, Ricci M, Esmail AA, Murad S, Marafi F, Treglia G, Khalaf AN, Anwar FM, Usmani S, Omar Y, Muhsin H, Tyurin IE, Zakhary A, Al-Sebaie S, Cortes DM, AlHashim M, Arabi H, Zaidi H.   +31 more
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Radar emitter identification with bispectrum and hierarchical extreme learning machine

Multimedia Tools and Applications, 2018
Radar Emitter Identification (REI) has been broadly used in military and civil fields. In this paper, a novel method is proposed for radar emitter signal identification, where the bispectrum estimation of radar signal is extracted and the recent hierarchical extreme learning machine (BS + H-ELM) is adopted for further feature learning and recognition ...
Jiuwen Cao, Jian-Ping Mei, Chun Yin
exaly   +3 more sources

A three-way incremental-learning algorithm for radar emitter identification

Frontiers of Computer Science, 2015
Radar emitter identification has been recognized as an indispensable task for electronic intelligence system. With the increasingly accumulated radar emitter intelligence and information, one key issue is to rebuild the radar emitter classifier efficiently with the newly-arrived information.
Wang Jianhong
exaly   +3 more sources

Radar Emitter Identification Using Hidden Markov Model

2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), 2019
Using the statistical signal processing principle, which is widely used in the field of natural language processing (NLP), a radar emitter identification (REI) approach based on hidden Markov model (HMM) is proposed. Since a radar emitter is modeled by three model parameters of a HMM, the REI can be solved from the solution of the evaluation problem of
Wei Zhang, Xin Yin, Xuyuan Cao, Yue Xie, Wei Nie   +4 more
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Specific Radar Emitter Identification Using 1D-CBAM-ResNet

2022 14th International Conference on Wireless Communications and Signal Processing (WCSP), 2022
With the development of the multifunction radar, the traditional specific emitter identification (SEI) can no longer meet the needs of the observe-orient-decide-act (OODA) closed loop, and most identification networks are in the process of converting one-
Jifei Pan, Linqing Guo, Qiuju Chen, Shengli Zhang, Jingwei Xiong   +4 more
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Identification of Radar Emitter Type with Recurrent Neural Networks

2020 Sensor Signal Processing for Defence Conference (SSPD), 2020
In this paper, we present a method for the identification of different multifunction radar emitter types. It is based on Long Short-Term Memory recurrent neural networks and a previously published hierarchical modelling approach. This approach maps radar pulses to different levels of symbols which can be regarded as parts of a radar language.
Sabine Apfeld, Alexander Charlish, Gerd Ascheid   +2 more
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Radar Emitter Identification Based on Novel Time-Frequency Spectrum and Convolutional Neural Network

IEEE Communications Letters, 2021
Radar emitter identification (REI) is significant in both military and civilian application domains. A critical step for REI is signal feature extraction.
Zhiling Xiao
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Radar Emitter Identification in Multistatic Radar System: A Review

2021
Due to the increasing complexity of modern multi-functional radars in the electromagnetic environment, it is a challenging task to classify and identify the presence of different radar emitters. The presence of multiple number of active transmitters in the multistatic radar system makes radar emitter identification a big data problem as all are ...
Dillip Dash, J. Valarmathi
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Radar Emitter Identification Based on Co-clustering and Transfer Learning

2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA), 2021
In recent years, artificial intelligence and machine learning have been used to identify radar emitters. However, there are two basic assumptions in traditional machine learning: (1) the data of training set and test set are independent and identically distributed.
Yuguo Peng, Yifang Zhang, Chunxia Chen, Ling Yang, Yongchun Li, Zhibin Yu   +5 more
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Radar Emitter Identification Based on Feedforward Neural Networks

2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), 2020
The aim of the article is implement radar emitter Identification. This paper applies neural network classifier in identification, and proposes a approach based on combination of multiple classifiers to improve the training efficiency. In the study, feedforward neural networks are utilized for identifying radar radiation sources, and the parameters of ...
Zhiling Xiao, Zhenya Yan
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