New beamforming method based on radial- basis function neural network processing in SαSG distribution noise environments

Daifeng Zha
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Abstract

This paper considers the beamforming problem with radial-basis function network in alpha stable noise environment. In the new noise environment, a novel training method is proposed based on covariation. Comparing the output of the network with the analytical solution, it is found that they are very consistent. Then, it is reasonable to perform beamforming by using radial-basis function network.
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s - α - sg分布噪声环境下基于径向基函数神经网络处理的波束形成新方法
研究了稳定噪声环境下径向基函数网络的波束形成问题。在新的噪声环境下,提出了一种基于协变的训练方法。将网络的输出与解析解进行比较,发现它们非常一致。因此,采用径向基函数网络进行波束形成是合理的。
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