Results 101 to 110 of about 350 (145)

Behavioral (reaction time) and prefrontal cortex response revealed differences in grief vs. sadness perception. [PDF]

Sci Rep
Tripathi S, Imai H, Adachi I.
europepmc   +1 more source

Artificial Intelligence-Based Wearable Sensing Technologies for the Management of Cancer, Diabetes, and COVID-19. [PDF]

Biosensors (Basel)
Kumar A, Goel S, Chaudhary A, Dutt S, Mishra VK, Kumar R.   +5 more
europepmc   +1 more source

Evaporation and transpiration processes and changes in their proportional relationships in cotton fields under varying degrees of film biodegradation. [PDF]

Front Plant Sci
Zhang H, Wang D, Zhang X, Lv Z, Jia T, Liu H, Wang Y, Lin T, Tang Q.   +8 more
europepmc   +1 more source

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A new recognition system for radar emitter signals

Kybernetes, 2012
PurposeThe purpose of this paper is to develop a new recognition system for identifying advanced radar emitter signals (RES).Design/methodology/approachInitially, the framework of the new recognition system is outlined. Then, feature extraction using resemblance coefficient and wavelet packet decomposition, and feature selection based on quantum ...
Gexiang Zhang
exaly   +2 more sources

Radar Emitter Recognition Based on LE-SVDD Classifier

2019 IEEE 2nd International Conference on Information Communication and Signal Processing (ICICSP), 2019
For existing radar emitter recognition method, the performance declines sharply with decreasing of training sample numbers. To overcome this problem, a LE-SVDD classifier is proposed and applied in radar emitter recognition. In the LE-SVDD classifier, Laplacian Eigenmaps (LE) algorithm, which belongs to manifold learning field, is employed to improve ...
Yan Mao, Guangxue Wang, Xiaoqiang Xu, Lirong Guo   +3 more
exaly   +2 more sources

A new radar emitter recognition method based on pulse sample figure

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011
Radar emitter recognition is the terminal purpose of radar signal processing. The classical recognition method based on feature extraction usually compares feature data of unrecognized radar signal with the data in database and then obtains emitter recognition result.
Chen Ting, Guo Wei, Shen Bing
exaly   +2 more sources

An Evaluation Method on Radar Emitter Signal Recognition Effect Based on SVM

2018 5th International Conference on Systems and Informatics (ICSAI), 2018
Radar emitter signal recognition is a key technology in electronic countermeasures and information processing. It is an essential part of scientific evaluation of its recognition effect. Aiming at the shortcomings that the evaluation index on the current radar emitter recognition effect is single, this paper constructs the mean and variance evaluation ...
Jun Han, Xiaojie Tang, Zhikai Tang, Juan Du   +3 more
exaly   +2 more sources

Research on technology of radar emitter recognition

Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826), 2005
Artificial intelligence technologies are introduced to radar countermeasure intelligence processing in recent years. Based on radar practical reconnaissance environment, several radar emitter recognition algorithms are studied in this paper. They are fuzzy comprehensive evaluation, gray correlation analysis, and fuzzy pattern recognition. In this paper,
null Xin Guan, null Xiao Yi, null You He
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Combining Multiple SVM Classifiers for Radar Emitter Recognition

2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009
Radar emitter recognition is of great importance in modern ELINT and ESM systems. The conventional methods for emitter recognition usually use one classifier. For specific emitter recognition, there are slight differences between the feature vectors from radars with the same type.
Lin Li 0050, Hongbing Ji
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Radar emitter signal recognition based on atomic decomposition

2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008
In this paper, a novel approach based on Gaussian Chirplet Atoms is presented to automatically recognise radar emitter signals. Firstly, based on the over-completed dictionary of Gaussian Chirplet atoms, the improved matching pursuit (MP) algorithm is applied to extract the features of the time-frequency atoms from the typical radar emitter signals ...
Ming Zhu, Weidong Jin, Laizhao Hu
openaire   +1 more source