A. Mansour, A. Kardec Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications.," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences,vol. E83-A, no. 8, pp. 1498--1512, 2000, Special Section on Digital Signal Processing in IEICE EA. 238  Home/Search Document Details and Download
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A Solution Procedure For Blind Signal Separation Using.. - Hundley, Kirby, Anderle (2001) (Correct)
....of Scientific Research grant F49620 99 1 0034 P00002. Actually, the problem is a special case of the generalized eigenvector problem with non negative definite matrices; hence, it is more properly viewed as a generalized singular value problem. using second order statistics is well known [7, 8], but the connection to MNF is not; in fact, the MNF algorithm itself does not seem to be widely known. The purpose of this paper is twofold: We will review MNF, then show that the variational problem produced will also yield independent components in the sense that we will implicitly compute the ....
A. Mansour, A. K. Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications, " IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E83A, no. 8, pp. 1498--1512, August 2000.
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A. Mansour, A. Kardec Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications.," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences,vol. E83-A, no. 8, pp. 1498--1512, 2000, Special Section on Digital Signal Processing in IEICE EA. 238
A Survey of the Performance Indexes of ICA Algorithms - MANSOUR, KAWAMOTO, OHNISHI (2002) (1 citation) Self-citation (Mansour Ohnishi) (Correct)
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A. Mansour, A. Kardec Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications. ," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E83-A, no. 8, pp. 1498--1512, August 2000.
A Time-Frequency Approach To Blind Separation Of.. - Mansour, Al. (2003) Self-citation (Mansour) (Correct)
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A. Mansour, A. Kardec Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications.," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E83-A, no. 8, pp. 1498--1512, August 2000.
A Simple ICA Algorithm Based on Geometrical Approach - Mansour, Puntonet, Ohnishi (2001) Self-citation (Mansour Ohnishi) (Correct)
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A. Mansour, A. Kardec Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications. ," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences,vol. E83-A, no. 8, pp. 1498--1512, 2000, Special Section on Digital Signal Processing in IEICE EA.
HOS Criteria & ICA Algorithms Applied to Radar Detection - Bouzaien, Mansour (2003) Self-citation (Mansour) (Correct)
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A. Mansour, A. Kardec Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications. ," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E83-A, no. 8, pp. 1498--1512, August 2000.
Batch Mutually Referenced Separation Algorithm for MIMO.. - Mansour Self-citation (Mansour) (Correct)
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A. Mansour, A. Kardec Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications.," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E83-A, no. 8, pp. 1498--1512, August 2000.
A Simple ICA Algorithm Based on Geometrical Approach. - Mansour, Puntonet, Ohnishi (2001) Self-citation (Mansour Ohnishi) (Correct)
....(HOS) Keywords: Blind Separation of Sources, ICA, PDF, Geometrical Methods, Decorrelation, Cholesky Factorization, Orthogonalization and Whitening process. 1 Introduction The blind separation of sources (BSS) is a recent and important problem in signal processing and it has many applications [1]. Since 1984 [2] it has been studied by many authors whilst many algorithms have been proposed. The blind separation of sources problem consists in retrieving unknown sources X(t) from only observing a mixture of them Y (t) 3, 4] see Fig. 1) In general case, authors assume that the sources are ....
....the covariance matrix of the mixing signals [21, 22] In the following, we consider only the case of instantaneous mixture with same number p of sources and sensors. On the other hand, it is known that the separation of instantaneous mixture can be achieved up to a permutation and a scale factor [5, 1] (i.e. the estimated sources S(t) are equal to the sources up to a permutation and a scale factor) Therefore the global matrix G = WM (W is the demixing matrix or the separating matrix) should satisfy the following: G = PD (1) where P is any permutation and D is any full rank diagonal matrix. ....
A. Mansour, A. Kardec Barros, and N. Ohnishi, "Blind separation of sources: Methods, assumptions and applications. ," IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E83-A, no. 8, pp. 1498--1512, 2000, Special Section on Digital Signal Processing in IEICE EA.
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