A contourlet domain sparse component analysis for blind image separation is proposed. An estimation algorithm for separation matrix is given based on the sparse description of the contourlet transform. The proposed algorithm is used to separate the mixed images. Simulation results show that the proposed approach is able to yield better separation performance for convergence speed, and the order...

Presented here is a generalization of the modified relative Newton method, recently proposed in [1] for quasi-maximum likelihood blind source separation. Special structure of the Hessian matrix allows to perform block-coordinate Newton descent, which significantly reduces the algorithm computational complexity and boosts its performance. Simulations based on artificial and real data show that t...

In blind source separation, there areM sources that produce sounds independently and continuously over time. These sounds are then recorded bym receivers. The sound recorded by each receiver at each time point is a linear superposition of the sounds produced by the M sources at the same time point. The problem of blind source separation is to recover the sounds of the sources from the sounds re...

Biological membranes constitute the set of membranes defining boundaries and organelles in living cells--the structural and functional building blocks of all known living organisms. The integrity of the cell depends on its ability to separate inside from outside and yet at the same time allow massive transport of matter in and out the cell. Nature has elegantly met this challenge by developing ...

Abstract—Many source separation methods use a two-stage procedure of first equalising the second order statistics of the data by a whitening process and then seeking a separation matrix for this whitened data. The second part of this procedure is in fact a question of finding the rotation matrix that maximises (or minimises, as appropriate) a higher order statistics performance criterion. We il...

Recently, developments in self-stabilized algorithms for gradient adaptation of orthonormal matrices have resulted in simple but powerful principal and minor subspace analysis methods. In this paper, we extend these ideas to develop algorithms for instantaneous prewhitened blind separation of homogeneous signal mixtures. Our algorithms are proven to be self-stabilizing to the Stiefel manifold o...

In this paper, we describe a new blind source separation (BSS) method that uses spatial information derived from the direction of arrival (DOA) estimates of each direct and reflected sound. The method we proposed has the following steps: (1) each DOA is estimated using matching pursuit and re-optimized after each new DOA is estimated, (2) using these DOA estimates, the mixing matrix is also est...

We propose a new perspective on speech communication using blind source separation. The original speech is mixed with key signals which consist of the mixing matrix, chaotic signals and a random noise. However, parts of the keys (the mixing matrix and the random noise) are not necessary in decryption. In practice implement, one can encrypt the speech by changing the noise signal every time. Hen...

For a directed acyclic graph, there are two known criteria to decide whether any specific conditional independence statement is implied for all distributions factorizing according to the given graph. Both criteria are based on special types of path in graphs. They are called separation criteria because independence holds whenever the conditioning set is a separating set in a graph theoretical s...