Separation of Sparse Signals in Overdetermined Linear-Quadratic Mixtures
نویسندگان
چکیده
In this work, we deal with the problem of nonlinear blind source separation (BSS). We propose a new method for BSS in overdetermined linear-quadratic (LQ) mixtures. By exploiting the assumption that the sources are sparse in a transformed domain, we define a framework for canceling the nonlinear part of the mixing process. After that, separation can be conducted by linear BSS algorithms. Experiments with synthetic data are performed to assess the viability of our proposal.
منابع مشابه
Morphological Diversity and Sparsity in Blind Source Separation
This paper describes a new blind source separation method for instantaneous linear mixtures. This new method coined GMCA (Generalized Morphological Component Analysis) relies on morphological diversity. It provides new insights on the use of sparsity for blind source separation in a noisy environment. GMCA takes advantage of the sparse representation of structured data in large overcomplete sig...
متن کاملBlind Separation of L Sources from M Mixtures of Speech Signals
In many real-world applications of blind source separation, the number of mixture signals, M available for analysis often differs from the number of sources, L which may be present. In this paper, we extend a successful and efficient kurtosis maximization algorithm used in speech separation of two sources from two linear mixtures for use in problems with arbitrary numbers of sources and mixture...
متن کاملBlind Source Separation of Overdetermined Linear-Quadratic Mixtures
This work deals with the problem of source separation in overdetermined linear-quadratic (LQ) models. Although the mixing model in this situation can be inverted by linear structures, we show that some simple independent component analysis (ICA) strategies that are often employed in the linear case cannot be used with the studied model. Motivated by this fact, we consider the more complex yet m...
متن کاملBlind Separation of Real World Audio Signals Using Overdetermined Mixtures
We discuss the advantages of using overdetermined mixtures to improve upon blind source separation algorithms that are designed to extract sound sources from acoustic mixtures. A study of the nature of room impulse responses helps us choose an adaptive lter architecture. We use ideal inverses of acquired room impulse responses to compare the eeectiveness of diierent-sized separating lter conngu...
متن کاملQuadratic independent component analysis
The transformation of a data set using a second-order polynomial mapping to find statistically independent components is considered (quadratic independent component analysis or ICA). Based on overdetermined linear ICA, an algorithm together with separability conditions are given via linearization reduction. The linearization is achieved using a higher dimensional embedding defined by the linear...
متن کامل