Title :
Target recognition study using SVM, ANNs and expert knowledge
Author :
Shi, Guangzhi ; Hu, Junchuan ; Da, Lianglong ; Song, Rugang
Author_Institution :
Dept. of Navig. & Commun., Navy Submarine Acad., Qingdao
Abstract :
An underwater acoustic target recognition system is researched. According to characteristic of the ship radiated-noise demodulation line spectrum feature and its training sample set, the target recognition system adopts four methods including expert system, neighbor method, SVM and RBF ANNs. And the target recognition system makes use of advantage of the four methods. Experiment results show that it has better recognition effect.
Keywords :
demodulation; expert systems; radial basis function networks; ships; support vector machines; telecommunication computing; underwater acoustic communication; RBF ANN; SVM; expert system; neighbor method; ship radiated-noise demodulation; underwater acoustic target recognition system; Artificial intelligence; Artificial neural networks; Expert systems; Multi-layer neural network; Neural networks; Neurons; Support vector machine classification; Support vector machines; Target recognition; Underwater acoustics; Demodulation line spectrum feature; Expert system; RBF ANNs; SVM; Underwater acoustic target recognition;
Conference_Titel :
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-2502-0
Electronic_ISBN :
978-1-4244-2503-7
DOI :
10.1109/ICAL.2008.4636392
