A fundamental trial on independent component analysis under the introduction of fuzzy theory

N. Kakasaki, K. Tsuruta, A. Ikuta, M. Ohta
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Abstract

The problem of independent component analysis and/or blind signal separation becomes a very popular and emerging field of research, because the problem contains many potential applications. In such a problem, a priori information we can utilize is the statistical independency between source signals. In many actual fields, the independent component analysis must play an essential role but it also contains problems: it cannot be applicable to non-physical quantity like a human psychological or sensory one, etc. This paper proposes a fundamental trial of independent component analysis by introducing the fuzzy theory. More precisely, the parameters of unknown system are estimated on the basis of fuzzy observations. Finally, the effectiveness of this method is confirmed through digital simulation.
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引入模糊理论的独立分量分析的基本尝试
独立分量分析和/或盲信号分离问题成为一个非常流行的新兴研究领域,因为该问题包含许多潜在的应用。在这种问题中,我们可以利用的先验信息是源信号之间的统计独立性。在许多实际领域中,独立分量分析必须发挥重要作用,但它也存在问题:不能适用于非物理量,如人的心理量或感官量等。本文通过引入模糊理论,提出了一种独立分量分析的基本方法。更精确地说,在模糊观测的基础上估计未知系统的参数。最后,通过数字仿真验证了该方法的有效性。
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