Radial basis function neural networks and temporal fusion for the classification of bioacoustic time series
نویسندگان
چکیده
In this paper, we discuss radial basis function (RBF) classi$ers and classi$er fusion architectures to categorize bioacoustic time series. The proposed methods are evaluated on a data base of cricket songs of 35 di;erent species recorded in Thailand and Ecuador. Local characteristic features are extracted from the recordings and then categorized by RBF classi$ers. These local decisions are then combined through temporal fusion. Three di;erent fusion techniques (Averaging, Percentiles and Voting) are considered. We present and discuss the classi$cation results for the proposed classi$er architectures on this data set of 35 species. c © 2002 Elsevier Science B.V. All rights reserved.
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عنوان ژورنال:
- Neurocomputing
دوره 51 شماره
صفحات -
تاریخ انتشار 2003