An audio separation system based on the neural ICA method

被引：0

作者：

Brát, M ^{[1
]}

Snorek, M ^{[1
]}

机构：

[1] Czech Tech Univ, Fac Elect Engn, Dept Comp Sci & Engn, Prague 12135 2, Czech Republic

来源：

ESM 2003: 17TH EUROPEAN SIMULATION MULTICONFERENCE: FOUNDATIONS FOR SUCCESSFUL MODELLING & SIMULATION | 2003年

关键词：

data mining; signal mining; blind signal separation; BSS; independent component analysis; ICA; fast Fourier transformation; FFT; principal component analysis; PCA; self-organizing map; SOM; learning vector quantization; LVQ;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This contribution deals with the problems based on data mining, especially signal mining. The main representative of signal mining is Blind Signal Separation. This group of problems can be solved by traditional (mathematical) methods or also untraditional techniques that utilize artificial intelligence such as neural networks. They are not possible to use alone, therefore this contribution focuses on pre-processing of input signals too. In conclusion we show our developed. system based on self-organizing neural network and several experiments with it.

引用

页码：557 / 561

页数：5