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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mishra, A.K. |
| Copyright Year | 2008 |
| Description | Author affiliation: ECE Dept., IIT Guwahati, Guwahati (Mishra, A.K.) |
| Abstract | Both principal component analysis (PCA) and linear discriminant analysis (LDA) have long been recognized as tools for feature extraction and data analysis. There has been reports in the open literature regarding the performance of both LDA and PCA as feature extractors in various types of classification and recognition problems. Many of the reports claim a better performance with LDA than with PCA. However, the grounds of comparison have mostly been quite narrow. In the current paper PCA and LDA based classifiers are evaluated for the problem of synthetic aperture radar based automatic target recognition problem. The results show that in terms of absolute performance, PCA outperforms LDA. Results of PCA based classifier are also found to be of higher confidence than those from LDA based classifiers, as observed from the error-bar analysis of the classifiers.With decreased amount of training dataset, the degradation in the performance of the classifiers are almost similar in nature. The current work concludes that LDA is not suitable for radar image based target recognition task. This is in line with reports from some works in the open literature which claim that the success of LDA will depend on the type of data and whether there is exhaustive data available during the training phase or not. |
| Sponsorship | IEEE Region 10 |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 131940 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424424085 |
| DOI | 10.1109/TENCON.2008.4766807 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-11-19 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Principal component analysis Linear discriminant analysis Feature extraction Target recognition Data analysis Data mining Error analysis Performance analysis Degradation Radar imaging SAR-ATR PCA LDA |
| Content Type | Text |
| Resource Type | Article |
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