کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536603 870574 2009 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classification of audio signals using Fuzzy c-Means with divergence-based Kernel
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Classification of audio signals using Fuzzy c-Means with divergence-based Kernel
چکیده انگلیسی

A content-based audio retrieval method based Fuzzy c-Means algorithm with divergence kernel (FCM-DK) is proposed in this paper. FCM-DK is based on the Fuzzy c-Means algorithm and employs a kernel method for data transformation. The kernel method adopted in FCM-DK is used to transform the feature data of audio signals into a feature space of a higher dimensionality so that nonlinear problems residing in the input space can be linearly solved in the feature space. In order to deal with Gaussian probability density function (GPDF) data, a divergence-based kernel employing a divergence distance measure for its similarity measure is used for data transformation. The proposed method exploits the statistical nature of the audio data to improve the classification accuracy. Experiments and results on various data sets demonstrate that the proposed classification method outperforms conventional algorithms such as the traditional self-organizing map (SOM) and the Fuzzy c-Means (FCM) 20.83% and 17.5% in terms of accuracy.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 30, Issue 9, 1 July 2009, Pages 794–798
نویسندگان
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