AN ADAPTIVE GEOMETRICAL PROCEDURE FOR BLIND SEPARATION OF SOURCES

被引：18

作者：

PUNTONET, CG ^{[1
]}

PRIETO, A ^{[1
]}

机构：

[1] UNIV GRANADA,FAC CIENCIAS,DEPT ELECTR & TECNOL COMPUTADORES,E-18071 GRANADA,SPAIN

来源：

NEURAL PROCESSING LETTERS | 1995年 / 2卷 / 05期

关键词：

D O I：

10.1007/BF02332162

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];

摘要：

In many Signal Processing applications, data sampled by sensors comprise a mixture of signals from different sources. The problem of blind separation lies in the reconstruction of sources from the mixtures. In this paper a new method is proposed for the separation of sources, based on geometrical considerations. After a brief introduction, we present the principles of the new method and provide a description of the algorithm and map this on an artificial neural network. Finally we give examples with synthetic and real signals to illustrate the efficiency and utility of the network

引用

页码：23 / 27

页数：5

共 9 条

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[8]

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[9]

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