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Generalized quadratic minimization and blind multichannel deconvolution

机译:广义二次最小化和盲多通道反卷积

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摘要

This paper deals with the problem of quadratic minimization subject to linear equality constraints. Unlike the standard formulation, we assume the most general case of a possibly singular quadratic form. We explain that the existing formal solution to this problem has several drawbacks. Our new approach is free from most of these drawbacks. In particular, it has a simple interpretation and is relatively easy to implement. The practical importance of this result lies in its numerous applications: filter design, spectral analysis, direction finding, and blind deconvolution of multiple FIR channels. Here, we focus on the blind deconvolution application for which we present a novel solution with enhanced performance.
机译:本文讨论受线性等式约束的二次最小化问题。与标准公式不同,我们假设最通用的情况可能是奇异的二次形式。我们解释说,解决该问题的现有形式解决方案有几个缺点。我们的新方法没有这些缺点中的大多数。特别地,它具有简单的解释并且相对容易实现。该结果的实际重要性在于其众多应用:滤波器设计,光谱分析,方向寻找和多个FIR通道的盲反卷积。在这里,我们专注于盲反卷积应用,为此我们提出了一种具有增强性能的新颖解决方案。

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