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| ROBUST BLIND NEURAL NETWORK BEAMFORMER BASED ON CYCLOSTATIONARY |
| He Zhenya; Chen Yuxin |
| Department of Radio Engineering Southeast University Nanjing 210096 |
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Abstract A new blind beamformer with improved Hopfield network is presented in this paper. To estimate the steering vector, the signal property of cyclostationary is used. To suppress interference, traditional LCMV beamforming is employed. To improve the robustness, diagonal loading technique is exploited. To turn into realization in real time, a neural network structure is given. Simulations demonstrate the excellent performance of the proposed approach in a wide variety of situations.
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Received: 22 June 1998
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2000, Vol. 22 
