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» Linear State-Space Models for Blind Source Separation
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JMLR
2006
105views more  JMLR 2006»
13 years 4 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
13 years 5 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»
13 years 9 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
13 years 5 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
13 years 10 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