Fast and robust adaptive beamforming method based on complex-valued RBF neural network

Fast and robust adaptive beamforming method based on complex-valued RBF neural network

The adaptive beamforming is one of the key techniques for array signal processing. However, the matrix inversion operation in the existing methods will cost a large amount of computational complexity, which results in poor real-time processing ability. In order to reduce the amount of computational...

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Bibliographic Details
Main Authors: Yuqing Li, Xiaopeng Yang, Feifeng Liu
Format: Article
Language:English
Published: Wiley 2019-07-01
Series:The Journal of Engineering
Subjects:
covariance matrices
array signal processing
matrix inversion
radial basis function networks
matrix inversion operation
computational complexity
real-time processing ability
computational cost
fast adaptive beamforming method
robust adaptive beamforming method
complex-valued radial basis function neural network
CRBF neural network
direct matrix inversion
nonlinear mapping processing
array covariance matrix
adaptive weight vector
simulation results
sample matrix inversion algorithm method
RBF neural network beamformer
complex-valued RBF neural network
key techniques
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0275

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https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0275

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