CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 11321 > Article
Paper
27 November 2019 Improved extreme learning machine and its application in SAR target recognition
Jian Chen
Author Affiliations +
Proceedings Volume 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence; 1132124 (2019) https://doi.org/10.1117/12.2543665
Event: The Second International Conference on Image, Video Processing and Artifical Intelligence, 2019, Shanghai, China
Abstract
In this paper, An improved algorithm for the extreme learning machine is proposed and applied to SAR target recognition.In order to solve the influence of the noise and spatial distribution of the training samples on the calculation of the classification plane, different penalty factors are given to different training samples, and according to this, the “weighted extreme learning machine” is proposed. And then,the kernel function is introduced into the "extreme learning machine" to improve the ability of nonlinear function approximation. Considering that the general training algorithm of the weighted extreme learning machine is slow and consumes a lot of computer memory when the number of training samples is large, a training method based on conjugate gradient algorithm is proposed. The test on "banana benchmark data" shows that the weighted extreme learning machine based on the conjugate gradient method can complete the convergence in the number of iterations far less than the number of samples, and the calculation speed is much faster than the traditional algorithm. Finally, this proposed algorithm is applied to SAR target recognition. The test on MSTAR data set shows that the proposed algorithm is not only extremely fast in SAR target recognition, but also has better recognition performance than support vector machine, general limit learning machine, BP neural network and other algorithms.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Jian Chen "Improved extreme learning machine and its application in SAR target recognition", Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 1132124 (27 November 2019); https://doi.org/10.1117/12.2543665
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 9 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Detection and tracking algorithms
Synthetic aperture radar
Target recognition
Evolutionary algorithms
Image filtering
Neural networks
Error analysis
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top