๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Content-based audio classification and segmentation by using support vector machines

โœ Scribed by Lie Lu; Hong-Jiang Zhang; Stan Z. Li

Publisher
Springer US
Year
2003
Tongue
English
Weight
508 KB
Volume
8
Category
Article
ISSN
0942-4962

No coin nor oath required. For personal study only.

๐Ÿ“œ SIMILAR VOLUMES

Fuzzy support vector machine for classif
Fuzzy support vector machine for classification of EEG signals using wavelet-based features
โœ Qi Xu; Hui Zhou; Yongji Wang; Jian Huang ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 815 KB

Translation of electroencephalographic (EEG) recordings into control signals for brain-computer interface (BCI) systems needs to be based on a robust classification of the various types of information. EEG-based BCI features are often noisy and likely to contain outliers. This contribution describes

Multi-fault classification based on supp
Multi-fault classification based on support vector machine trained by chaos particle swarm optimization
โœ Xianlun Tang; Ling Zhuang; Jun Cai; Changbing Li ๐Ÿ“‚ Article ๐Ÿ“… 2010 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 263 KB

A novel method of training support vector machine (SVM) by using chaos particle swarm optimization (CPSO) is proposed. A multi-fault classification model based on the SVM trained by CPSO is established and applied to the fault diagnosis of rotating machines. The results show that the method of train