Plate IV.695 · Publications
Sparse Component Analysis and Blind Source Separation of Underdetermined Mixtures
Article in IEEE Transactions on Neural Networks, July 2005.
Abstract
In this letter, we solve the problem of identifying matrices S is an element of R(n x N) and A is an element of R(m x n) knowing only their multiplication X = AS, under some conditions, expressed either in terms of A and sparsity of S (identifiability conditions), or in terms of X (sparse component analysis (SCA) conditions). We present algorithms for such identification and illustrate them by examples.
Cite
@article{georgiev2005sparse,
title = {{Sparse Component Analysis and Blind Source Separation of Underdetermined Mixtures}},
author = {Georgiev, P. and Theis, F. and Cichocki, A.},
journal = {IEEE Transactions on Neural Networks},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
year = {2005},
month = jul,
doi = {10.1109/tnn.2005.849840},
url = {https://doi.org/10.1109/tnn.2005.849840},
pmid = {16121741}
}