Complexity Pursuit: Using Both Nongaussianity and Autocorrelations for Signal Separation

Aapo Hyvärinen

Complexity Pursuit: Using Both Nongaussianity and Autocorrelations for Signal Separation

Aapo Hyvärinen

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Original language	English
Title of host publication	International Conference on Neural Information Processing (ICONIP'00), Taejon, Korea, Nov. 14-18, 2000
Pages	1198-1203
Publication status	Published - 2000
MoE publication type	A4 Conference publication

Keywords

blind source separation
higher-order statistics
independent component analysis

Cite this

@inproceedings{3dfd2cca3de2441a9bbb0889f1850ac1,

title = "Complexity Pursuit: Using Both Nongaussianity and Autocorrelations for Signal Separation",

keywords = "blind source separation, higher-order statistics, independent component analysis, blind source separation, higher-order statistics, independent component analysis, blind source separation, higher-order statistics, independent component analysis",

author = "Aapo Hyv{\"a}rinen",

year = "2000",

language = "English",

pages = "1198--1203",

booktitle = "International Conference on Neural Information Processing (ICONIP'00), Taejon, Korea, Nov. 14-18, 2000",

}

TY - GEN

T1 - Complexity Pursuit: Using Both Nongaussianity and Autocorrelations for Signal Separation

AU - Hyvärinen, Aapo

PY - 2000

Y1 - 2000

KW - blind source separation

KW - higher-order statistics

KW - independent component analysis

KW - blind source separation

KW - higher-order statistics

KW - independent component analysis

KW - blind source separation

KW - higher-order statistics

KW - independent component analysis

M3 - Conference article in proceedings

SP - 1198

EP - 1203

BT - International Conference on Neural Information Processing (ICONIP'00), Taejon, Korea, Nov. 14-18, 2000

ER -