Kernel multi-metric learning for multi-channel transient acoustic signal classification

Abstract

In this paper, we propose a kernel multi-metric learning algorithm for multi-channel transient acoustic signal classification. The proposed method learns a set of metrics jointly for multi-channel transient acoustic signals in a kernel-induced feature space to exploit the non-linearity of the data for improving the classification performance. An effective… (More)
DOI: 10.1109/ICASSP.2012.6288297

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@article{Zhang2012KernelML, title={Kernel multi-metric learning for multi-channel transient acoustic signal classification}, author={Haichao Zhang and Yanning Zhang and Nasser M. Nasrabadi and Thomas S. Huang}, journal={2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year={2012}, pages={1989-1992} }