Pairwise classification and support vector machines
Advances in kernel methods
The Journal of Machine Learning Research
In Defense of One-Vs-All Classification
The Journal of Machine Learning Research
Discretization of continuous attributes in rough set theory and its application
CIS'04 Proceedings of the First international conference on Computational and Information Science
Support vector machines with huffman tree architecture for multiclass classification
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
Content-based audio classification and retrieval by support vector machines
IEEE Transactions on Neural Networks
Improved quantum-inspired genetic algorithm based time-frequency analysis of radar emitter signals
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Intra-pulse modulation recognition of unknown radar emitter signals using support vector clustering
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
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A new method is proposed to solve the difficult problem of advanced radar emitter signal (RES) recognition. Different from traditional five-parameter method, the method is composed of feature extraction, feature selection using rough set theory and combinatorial classifier. Support vector clustering, support vector classification and Mahalanobis distance are integrated to design an efficient combinatorial classifier. 155 radar emitter signals with 8 intra-pulse modulations are used to make simulation experiments. It is proved to be a valid and practical method