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» Linear State-Space Models for Blind Source Separation
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JMLR
2006
105views more  JMLR 2006»
9 years 5 months ago
Linear State-Space Models for Blind Source Separation
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
Rasmus Kongsgaard Olsson, Lars Kai Hansen
NIPS
2004
9 years 7 months ago
A Harmonic Excitation State-Space Approach to Blind Separation of Speech
We discuss an identification framework for noisy speech mixtures. A block-based generative model is formulated that explicitly incorporates the time-varying harmonic plus noise (H...
Rasmus Kongsgaard Olsson, Lars Kai Hansen
ISCAS
2002
IEEE
109views Hardware» more  ISCAS 2002»
9 years 10 months ago
State space blind source recovery for mixtures of multiple source distributions
The paper discusses State Space Blind Source Recovery (BSR) for minimum phase and non-minimum phase mixtures of gaussian and non-gaussian distributions. The State Space Natural Gr...
Khurram Waheed, Fathi M. Salam
ESANN
2004
9 years 7 months ago
Separability of analytic postnonlinear blind source separation with bounded sources
The aim of blind source separation (BSS) is to transform a mixed random vector such that the original sources are recovered. If the sources are assumed to be statistically independ...
Fabian J. Theis, Peter Gruber
ICA
2004
Springer
9 years 11 months ago
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Fabian J. Theis, Shun-ichi Amari
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