APPROACH FOR APPROXIMATION OF SIGNAL SUBSPACE VIA NEURAL NETWORKS

Lin Sheng; Yin Qinye

Volume 17 Issue 1

Jan. 1995

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Lin Sheng, Yin Qinye. APPROACH FOR APPROXIMATION OF SIGNAL SUBSPACE VIA NEURAL NETWORKS[J]. Journal of Electronics & Information Technology, 1995, 17(1): 1-6.

Citation:

Lin Sheng, Yin Qinye. APPROACH FOR APPROXIMATION OF SIGNAL SUBSPACE VIA NEURAL NETWORKS[J]. Journal of Electronics & Information Technology, 1995, 17(1): 1-6.

Lin Sheng, Yin Qinye. APPROACH FOR APPROXIMATION OF SIGNAL SUBSPACE VIA NEURAL NETWORKS[J]. Journal of Electronics & Information Technology, 1995, 17(1): 1-6.

Citation:

Lin Sheng, Yin Qinye. APPROACH FOR APPROXIMATION OF SIGNAL SUBSPACE VIA NEURAL NETWORKS[J]. Journal of Electronics & Information Technology, 1995, 17(1): 1-6.

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APPROACH FOR APPROXIMATION OF SIGNAL SUBSPACE VIA NEURAL NETWORKS

Received Date: 1994-02-01
Rev Recd Date: 1994-07-12
Publish Date: 1995-01-19

Abstract

Abstract

A neural method to solve the orthogonality search problem arising in direction-of-arrival (DOA) estimation is proposed. The problem is mapped onto the snergy function of the neural network as a linear programming problem. The most important feature of this method hinges upon the fact that the number of neurons in the network is linearly dependent on the number of sensors in the sensor array, rather than the discretization levels of parameter space. Theoretical analysis and simulation results show that the p...

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References(1)

References

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