Bayesian signal classifier

被引：0

作者：

Chow, Chi Kin ^{[1
]}

Yuen, Shiu Yin ^{[1
]}

机构：

[1] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China

来源：

2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6 | 2007年

关键词：

D O I：

10.1109/IJCNN.2007.4370956

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article points out the limitations of vectoral input pattern on density estimation and Bayesian classification. A continuous Bayesian classifier is proposed to tackle these limitations. The classifier accepts signal as input pattern; thus the problem of optimal description length selection is avoided. The algorithm is evaluated on signal clustering and distribution classification.

引用

页码：207 / 212

页数：6

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