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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Li Yujie Wang Wenguang Sun Jinping |
| Copyright Year | 2009 |
| Abstract | In this paper, based on the prior knowledge of chaotic character of sea clutter, we discuss a method for detection of small target in sea clutter using neural network as a predictor. Neural network can capture the dynamics of strange attractor generating sea clutter. After the reconstruction of real-life Radar data, BP and RBF networks are regularized, and then a set of sample data from real-life data is inputted into the networks to train the neural networks respectively. As a sequence, according the nature of neural networks, these trained networks could approximate the model of dynamical system responsible for sea clutter. These networks can be used to detect small target within sea clutter as a predictor. |
| Starting Page | 469 |
| Ending Page | 472 |
| File Size | 375206 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769536828 |
| DOI | 10.1109/ESIAT.2009.60 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-04 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Chaos chaos Predictive models Function approximation Clutter Sun sea clutter neural network Neural networks Radar detection Character generation Object detection Radial basis function networks small target detection |
| Content Type | Text |
| Resource Type | Article |
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