Abstract
Convolutional neural network (CNN) has become a promising method for Synthetic aperture radar (SAR) target recognition. Existing CNN models aim at seeking the best separation between classes, but rarely care about the separability of them. We performs a separability measure by analyzing the property of linear separability, and proposes an objective function for CNN to extract linearly separable features. The experimental results indicate the output features are linearly separable, and the classification results are comparable with the other state of the art techniques.
Original language | English |
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Pages (from-to) | 423-429 |
Number of pages | 7 |
Journal | CHINESE JOURNAL OF ELECTRONICS |
Volume | 28 |
Issue number | 2 |
DOIs | |
Publication status | Published - 01 Mar 2019 |
Externally published | Yes |
Bibliographical note
Funding Information:∗Manuscript Received Apr. 12, 2018; Accepted Aug. 11, 2018. This research was funded by the National Natural Science Foundation of China (No.61771027, No.61071139, No.61471019, No.61501011, No.61171122). E. Yang is supported in part under the RSE-NNSFC Joint Project (2017-2019) (No.6161101383) with China University of Petroleum (Huadong). H. Zhou is supported by Invest NI/Philips, UK EPSRC (No.EP/N011074/1) and Royal Society-Newton Advanced Fellowship (No.NA160342). © 2019 Chinese Institute of Electronics. DOI:10.1049/cje.2018.12.001
Funding Information:
This research was funded by the National Natural Science Foundation of China (No.61771027, No.61071139, No.61471019, No.61501011, No.61171122). E. Yang is supported in part under the RSE-NNSFC Joint Project (2017-2019) (No.6161101383) with China University of Petroleum (Huadong). H. Zhou is supported by Invest NI/Philips, UK EPSRC (No.EP/N011074/1) and Royal Society-Newton Advanced Fellowship (No.NA160342).
Publisher Copyright:
© 2019 Chinese Institute of Electronics.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
Keywords
- Classification
- Convolution neural network (CNN)
- Linear separability
- Objective function
- Synthetic aperture radar (SAR)
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Applied Mathematics