Non-unitary matrix joint diagonalization for complex independent vector analysis
نویسندگان
چکیده
منابع مشابه
Non-Unitary Matrix Joint Diagonalization for Complex Independent Vector Analysis
Independent vector analysis (IVA) is a special form of independent component analysis (ICA), which has demonstrated its prominent performance in solving convolutive blind source separation (BSS) problems in the frequency domain. Most IVA algorithms are based on optimizing certain contrast functions, where the main difficulty of these approaches lies in finding a reliable and fast estimation of ...
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Independent Vector Analysis (IVA) is a special form of Independent Component Analysis (ICA) in terms of group signals. Most IVA algorithms are developed via optimizing certain contrast functions. The main difficulty of these contrast function based approaches lies in estimating the unknown distribution of sources. On the other hand, tensorial approaches are efficient and richly available to the...
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Non-unitary joint diagonalization of complex symmetric matrices is an important technique in signal processing. The so-called complex oblique projective (COP) manifold has been shown to be an appropriate manifold setting for analyzing the problem and developing geometric algorithms for minimizing the off-norm cost function. However, the recent identification of the COP manifold as a collection ...
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In this work, we consider block-Jacobi methods with Newton steps in each subspace search and prove their local quadratic convergence to a local minimum with non-degenerate Hessian under some orthogonality assumptions on the search directions. Moreover, such a method is exemplified for non-unitary joint matrix diagonalization, where we present a block-Jacobi-type method on the oblique manifold w...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2012
ISSN: 1687-6180
DOI: 10.1186/1687-6180-2012-241