Comparison of Lagrange constrained neural network with traditional ICA methods

被引：6
|
作者：
Szu, H [1 ]
Kopriva, I [1 ]
机构：
[1] George Washington Univ, Digital Media RF Lab, ECE Dept, Washington, DC 20052 USA
来源：
PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 | 2002年
关键词：
D O I：
10.1109/IJCNN.2002.1005517
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper presents comparison between the a priori MaxEnt and the a posteriori MaxEnt methodologies, namely Lagrange Constraint Neural Network (LCNN) by Szu in 1997 and ICA algorithms by Bell-Sejnowski-Amari-Oja (BSAO) and many others since 1996. We chose the remote sensing application because it is the only real world application that we know to be truly linear, single path, and instantaneous mixing of the unknown ground spectral objects.
引用
收藏
页码：466 / 471
页数：2
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