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Independent Component Analysis.

Seungjin Choi
- pp 435-459
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TLDR
The standardization of the IC model is talked about, and on the basis of n independent copies of x, the aim is to find an estimate of an unmixing matrix Γ such that Γx has independent components.
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The article was published on 2012-01-01 and is currently open access. It has received 2296 citations till now. The article focuses on the topics: Independent component analysis.

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ERPLAB: an open-source toolbox for the analysis of event-related potentials

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Handbook of Blind Source Separation: Independent Component Analysis and Applications

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GraRep: Learning Graph Representations with Global Structural Information

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References
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Proceedings ArticleDOI

Differential learning and random walk model

Seungjin Choi
TL;DR: First the algorithm is derived from the minimization of the objective function which measures the differential correlation, and it is shown that the differential decorrelation learning algorithm can also be derived in the framework of maximum likelihood estimation of a linear generative model with assuming a random walk model for latent variables.
Proceedings Article

Two-stage blind source separation combining SIMO-model-based ICA and adaptive beamforming

TL;DR: The proposed two-stage blind source separation for convolutive mixtures of speech is proposed, in which a Single-Input Multiple-Output (SIMO)-model-based ICA and an adaptive beamforming (ABF) are combined, and the experimental results reveal that the separation performance can be considerably improved by using the proposed method.
Proceedings ArticleDOI

Blind source separation based on binaural ICA

TL;DR: The experimental results reveal that the signal separation performance of the proposed binaural ICA is the same as that of the conventional ICA-based method; and the spatial quality of the separated sound in BICA is remarkably superior to that ofThe conventional method, especially for the fidelity of the sound reproduction.
Proceedings ArticleDOI

Blind separation and deconvolution of MIMO system driven by colored inputs using SIMO-model-based ICA with information-geometric learning

TL;DR: A new two-stage blind separation and deconvolution algorithm for multiple-input multiple-output (MIMO)- FIR system driven by colored sound sources, in which a new single- input multiple- output (SIMO)-model-based ICA ( SIMO-ICA) and blind multichannel inverse filtering are combined.

Two-Stage Blind Source Separation Using SIMO-ICA and Binary Masking

TL;DR: HSCMA2005: Joint Workshop on Hands-Free Speech Communication and Microphone Arrays, March 2005.