Paper Info
Title
Speech Separation Based on Higher Order Statistics Using Recurrent Neural Networks
Abstract
Independent Component Analysis (ICA) (Comon, 1994; Lee, 1998; Karhunen et al,1997; Haykin, 1998) is an unsupervised technique, which tries to represent the data in terms of statistically independent variables. ICA and the related blind source separation (BSS) and application topics both in unsupervised neural learning and statistical signal processing.
Year
DOI
Venue
2001
10.1007/978-3-7908-1782-9_5
HYBRID INFORMATION SYSTEMS
Keywords
Field
DocType
recurrent neural network
Pattern recognition,Computer science,Higher-order statistics,Recurrent neural network,Time delay neural network,Artificial intelligence,Independent component analysis,Statistical signal processing,Deep learning,Blind signal separation,Independence (probability theory),Machine learning
Conference
ISSN
Citations 
PageRank 
1615-3871
0
0.34
References 
Authors
9
2
Name
Order
Citations
PageRank
Yan Li120.73
David M. W. Powers250067.39