Optimal Linear Combination of Neural Networks for Improving Classification Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminative feature weighting for HMM-based continuous speech recognizers
Speech Communication
FS_SFS: A novel feature selection method for support vector machines
Pattern Recognition
Dual-population based coevolutionary algorithm for designing RBFNN with feature selection
Expert Systems with Applications: An International Journal
A filter based feature selection approach using lempel ziv complexity
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
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Motivated by the development of discriminative feature extraction (DFE), many researchers have come to realize the importance of designing a front-end feature extraction unit with an appropriate link to backend classification. This paper proposes an advanced formalization of DFE, which we call the discriminative metric design (DMD), and elaborates on its exemplar implementation by using a simple, linear feature transformation matrix. The resulting DMD implementation is shown to have a close relationship to various discriminative pattern recognizers, including artificial neural networks. The utility of the proposed method is clearly demonstrated in speech pattern recognition experiments