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文件名称:ANN-for-Blind-Source-Separation
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提出一种新的盲分离标准，基于这种标准构建横向反馈的线性前馈神经网路，并给出理论分析与实验结果-We presents a new necessary and sufficient condition for
the blind separation of sources having non-zero kurtosis,
from their linear mixtures. It is shown here that a new
blind separation criterion based on both odd (
)
and even (
) functions, presents desirable solutions,
provided that all source signals have negative kurtosis
(sub-Gaussian) or have positive kurtosis (super-Gaussian).
Based on this new separation criterion, a linear feedforward
network with lateral feedback connections is constructed.
Both theoretical and computer simulation results
are presented.
the blind separation of sources having non-zero kurtosis,
from their linear mixtures. It is shown here that a new
blind separation criterion based on both odd (
)
and even (
) functions, presents desirable solutions,
provided that all source signals have negative kurtosis
(sub-Gaussian) or have positive kurtosis (super-Gaussian).
Based on this new separation criterion, a linear feedforward
network with lateral feedback connections is constructed.
Both theoretical and computer simulation results
are presented.
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ANN for Blind Source Separation.pdf
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