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ICIP
2005
IEEE
16 years 1 months ago
Largest-eigenvalue-theory for incremental principal component analysis
In this paper, we present a novel algorithm for incremental principal component analysis. Based on the LargestEigenvalue-Theory, i.e. the eigenvector associated with the largest ei...
Shuicheng Yan, Xiaoou Tang
IDA
2009
Springer
15 years 6 months ago
Estimating Phase Linearity in the Frequency-Domain ICA Demixing Matrix
We consider a method for solving the permutation problem in blind source separation (BSS) by the frequency-domain independent component analysis (FD-ICA) by using phase linearity o...
Keisuke Toyama, Mark D. Plumbley
DIS
2007
Springer
15 years 5 months ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...
ICPR
2006
IEEE
16 years 23 days ago
ICA-Based Clustering for Resolving Permutation Ambiguity in Frequency-Domain Convolutive Source Separation
Permutation ambiguity is an inherent limitation in independent component analysis, which is a bottleneck in frequency-domain methods of convolutive source separation. In this pape...
Minje Kim, Seungjin Choi
NCA
2007
IEEE
14 years 11 months ago
Handling of incomplete data sets using ICA and SOM in data mining
Based on independent component analysis (ICA) and self-organizing maps (SOM), this paper proposes an ISOM-DH model for the incomplete data’s handling in data mining. Under these ...
Hongyi Peng, Siming Zhu