A connectionist method for pattern classification with diverse features

doi:10.1016/S0167-8655(98)00055-5

CORC > 北京大学 > 信息科学技术学院

	A connectionist method for pattern classification with diverse features
	Chen, K
刊名	pattern recognition letters
	1998
关键词	classification with diverse features mixture of experts Expectation-Maximization (EM) algorithm soft competition speaker identification EM ALGORITHM SYSTEMS
DOI	10.1016/S0167-8655(98)00055-5
英文摘要	A novel connectionist method is proposed to simultaneously use diverse features in an optimal way for pattern classification. Unlike methods of combining multiple classifiers, a modular neural network architecture is proposed through use of soft competition among diverse features. Parameter estimation in the proposed architecture is treated as a maximum likelihood problem, and an Expectation-Maximization (EM) learning algorithm is developed for adjusting the parameters of the architecture. Comparative simulation results are presented for the real world problem of speaker identification. (C) 1998 Elsevier Science B.V. All rights reserved.; Computer Science, Artificial Intelligence; SCI(E); 16; ARTICLE; 7; 545-558; 19
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/216966]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Chen, K. A connectionist method for pattern classification with diverse features[J]. pattern recognition letters,1998.
APA	Chen, K.(1998).A connectionist method for pattern classification with diverse features.pattern recognition letters.
MLA	Chen, K."A connectionist method for pattern classification with diverse features".pattern recognition letters (1998).