Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization
نویسندگان
چکیده
This paper deals with estimation of structured signals such as damped sinusoids, exponentials, polynomials, and their products from single channel data. It is shown that building tensors from this kind of data results in tensors with hidden block structure which can be recovered through the tensor diagonalization. The tensor diagonalization means multiplying tensors by several matrices along its modes so that the outcome is approximately diagonal or block-diagonal of 3-rd order tensors. The proposed method can be applied to estimation of parameters of multiple damped sinusoids, and their products with polynomial.
منابع مشابه
Blind Source Separation of fMRI Signals Using Joint Diagonalization Algorithm
Blind Source Separation (BSS) is a model free source separation technique which decomposes observed mixture data into mixing matrix and source matrix both of which are unknown beforehand. One well known BSS algorithm is joint diagonalization which is from the algebraic class and in which mixing structures are recovered by jointly diagonalizing the source condition matrix. In this study we first...
متن کاملOn The Use of Non-orthogonal Approximate Joint Diagonalization Algorithms for Blind Source Separation in Presence of Additive Noise
We present in this paper a non-orthogonal algorithm for the approximate joint diagonalization of a set of matrices. It is an iterative algorithm, using relaxation technique applied on the rows of the diagonalizer. The performances of our algorithm are compared with usual standard algorithms using blind sources separation simulations results. We show that the improvement in estimating the separa...
متن کاملA Unifying Criterion for Blind Source Separation and Decorrelation: Simultaneous Diagonalization of Correlation Matrices
Blind source separation and blind output decorrelation are two well-known problems in signal processing. For instantaneous mixtures, blind source separation is equivalent to a generalized eigen-decomposition, while blind output decorrelation can be considered as an iterative method of output orthogonalization. We propose a steepest descent procedure on a new cost function based on the Frobenius...
متن کاملTensor based source separation for single and multichannel signals
Blind source separation (BSS) techniques have the aim of separating original source signals from their mixtures without having or with a little knowledge about the source signals or the mixing process. Tensor based source separation techniques have become increasingly popular for various applications since they exploit different inherent diversities of the sources. Therefore, they can improve t...
متن کاملBlind identification of a linear-quadratic mixture of independent components based on joint diagonalization procedure
In this paper, we address the problem of the blind identii-cation of linear-quadratic instantaneous mixture of statistically independent random variables. This problem consists in the identiication of an unknown linear-quadratic transmission channel excited by temporally correlated and mutually independent source signals, using only statistical information on the observations received by an arr...
متن کامل