Direction Finding Using GHA Neural Networks
This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take sig...
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| Formato: | article |
| Lenguaje: | EN |
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Al-Khwarizmi College of Engineering – University of Baghdad
2017
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| Acceso en línea: | https://doaj.org/article/c8f3a72fdec44a29a67afcaa68d0fd16 |
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| Sumario: | This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).
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