Blind extraction of singularly mixed source signals
Blind extraction of singularly mixed source signals
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DOI：
10.1109/72.883467
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发表时间：
2000-11
影响因子：
--
通讯作者：
Yuanqing Li;Jun Wang;J. Zurada
中科院分区：
文献类型：
--
作者：
Yuanqing Li;Jun Wang;J. Zurada
本文提出了一种新的奇异源序列盲提取方法。首先，介绍了单源盲提取的神经网络模型和自适应算法。其次，对奇异混合矩阵进行了可抽取分析，得到了两组可抽取的充要条件。在此基础上提出了序贯盲提取的自适应算法和神经网络模型。讨论了该算法的稳定性。仿真结果验证了自适应算法的有效性和稳定性分析。该算法既适用于非奇异混合矩阵的情况，也适用于奇异混合矩阵的情况。
This paper introduces a novel technique for sequential blind extraction of singularly mixed sources. First, a neural-network model and an adaptive algorithm for single-source blind extraction are introduced. Next, extractability analysis is presented for singular mixing matrix, and two sets of necessary and sufficient extractability conditions are derived. The adaptive algorithm and neural-network model for sequential blind extraction are then presented. The stability of the algorithm is discussed. Simulation results are presented to illustrate the validity of the adaptive algorithm and the stability analysis. The proposed algorithm is suitable for the case of nonsingular mixing matrix as well as for singular mixing matrix.