基于特征值分解的彩色信号多通道盲反卷积

P. Georgiev, A. Cichocki
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引用次数: 5

摘要

我们证明了n个彩色不相关信号的MIMO(多输入多输出)盲反卷积问题可以转化为n个SIMO(单输入多输出)问题,使用依赖于l维参数b的特殊协方差矩阵的特征值分解,如果适当的协方差矩阵具有空成对相交的特征值集。我们给出了这种转换的充分条件,并讨论了如何结束这种参数。我们证明了这是可能的参数b,形成IR/sup L/的一个开放子集,其补具有勒贝格测度为零。
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Multichannel blind deconvolution of colored signals via eigenvalue decomposition
We prove that a MIMO (multiple input multiple output) blind deconvolution problem for n colored uncorrelated signals can be converted to n SIMO (single input multiple output) problems, using eigenvalue decomposition of a special covariance matrix, depending on L-dimensional parameter b, if appropriate covariance matrices have sets of eigenvalues with empty pairwise intersection. We present a sufficient condition for this conversion and discuss how to End such parameters. We prove that the parameters b for which this is possible, form an open subset of IR/sup L/, whose complement has a Lebesgue measure zero.
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期刊介绍: Journal of Signal Processing is an academic journal supervised by China Association for Science and Technology and sponsored by China Institute of Electronics. The journal is an academic journal that reflects the latest research results and technological progress in the field of signal processing and related disciplines. It covers academic papers and review articles on new theories, new ideas, and new technologies in the field of signal processing. The journal aims to provide a platform for academic exchanges for scientific researchers and engineering and technical personnel engaged in basic research and applied research in signal processing, thereby promoting the development of information science and technology. At present, the journal has been included in the three major domestic core journal databases "China Science Citation Database (CSCD), China Science and Technology Core Journals (CSTPCD), Chinese Core Journals Overview" and Coaj. It is also included in many foreign databases such as Scopus, CSA, EBSCO host, INSPEC, JST, etc.
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