منابع مشابه
The squared symmetric FastICA estimator
In this paper we study the theoretical properties of the deflation-based FastICA method, the original symmetric FastICA method, and a modified symmetric FastICA method, here called the squared symmetric FastICA. This modification is obtained by replacing the absolute values in the FastICA objective function by their squares. In the deflation-based case this replacement has no effect on the esti...
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In this paper, we propose to use the Huber M -estimator cost function as a contrast function within the complex FastICA algorithm of Bingham and Hyvarinen for the blind separation of mixtures of independent, non-Gaussian, and proper complex-valued signals. Sufficient and necessary conditions for the local stability of the complex-circular FastICA algorithm for an arbitrary cost are provided. A ...
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The goal of blind source separation is to separate multiple signals from linear mixtures without extensive knowledge about the statistical properties of the unknown signals. The design of separation criteria that achieve accurate and robust source estimates within a simple adaptive algorithm is an important part of this task. The purpose of this paper is threefold: (1) We introduce the Huber M-...
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Let f n,K denote a kernel estimator of a density f in R such that R f p (x)dx<∞ for some p>2. It is shown, under quite general conditions on the kernel K and on the window sizes, that the centered integrated squared deviation of f n,K from its mean, f n,K −Ef n,K 2 2 −Ef n,K −Ef n,K 2 2 satisfies a law of the iterated logarithm. This is then used to obtain an LIL for the deviation from the true...
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Independent component analysis (ICA) is possibly the most widespread approach to solve the blind source separation problem. Many different algorithms have been proposed, together with several highly successful applications. There is also an extensive body of work on the theoretical foundations and limits of the ICA methodology. One practical concern about the use of ICA with real world data is ...
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ژورنال
عنوان ژورنال: Signal Processing
سال: 2017
ISSN: 0165-1684
DOI: 10.1016/j.sigpro.2016.08.028