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ICIP
2005
IEEE
15 years 11 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
104
Voted
BMCBI
2010
149views more  BMCBI 2010»
14 years 9 months ago
A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context
Background: Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex eti...
Ioannis K. Valavanis, Stavroula G. Mougiakakou, Ke...
ICA
2010
Springer
14 years 10 months ago
Adaptive Underdetermined ICA for Handling an Unknown Number of Sources
Independent Component Analysis is the best known method for solving blind source separation problems. In general, the number of sources must be known in advance. In many cases, pre...
Andreas Sandmair, Alam Zaib, Fernando Puente Le&oa...
ICASSP
2009
IEEE
15 years 4 months ago
A multistage approach for blind separation of convolutive speech mixtures
In this paper, we propose a novel algorithm for the separation of convolutive speech mixtures using two-microphone recordings, based on the combination of independent component an...
Tariqullah Jan, Wenwu Wang, DeLiang Wang
71
Voted
ISCAS
2005
IEEE
131views Hardware» more  ISCAS 2005»
15 years 3 months ago
Blind signal separation into groups of dependent signals using joint block diagonalization
— Multidimensional or group independent component analysis describes the task of transforming a multivariate observed sensor signal such that groups of the transformed signal com...
Fabian J. Theis