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The performance of simplified CGM-BOPA in noisy environment adaptive processing

机译：简化的CGM-BOPA在嘈杂环境中的性能自适应处理

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Block orthogonal algorithm using conjugate gradient method has the advantage of a very good convergence characteristic only environment without noise, but known conditions become very unstable because convergence accuracy is corrupted under the noisy environment. Accordingly, optimal repetition number of the algorithm of CGM-BOPA is achieved with reduced computational requirement, and convergence characteristic is improved under the noisy environment. In this paper, in order to get repetition number, we analysed simplified CGM-BOPA (SCGM-BOPA). The performance of the proposed algorithm is shown by analysis and computer simulation.

机译：使用共轭梯度法的块正交算法的优点是仅在没有噪声的环境下具有很好的收敛特性，但是已知条件变得非常不稳定，因为在嘈杂的环境下收敛精度会受到破坏。因此，在减少计算需求的情况下，实现了CGM-BOPA算法的最佳重复次数，并且在嘈杂的环境下改善了收敛特性。在本文中，为了获得重复数，我们分析了简化的CGM-BOPA（SCGM-BOPA）。分析和计算机仿真表明了该算法的性能。

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《》|1999年|P.227-230|共4页
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Okamoto; M.; Nishikawa; Y.;
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中图分类无线电电子学、电信技术;
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The performance of simplified CGM-BOPA in noisy environment adaptive processing

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