Automatically assigned DDC number: 00632

Manually assigned DDC number: 00632

Number of references: 4

Title: Neural Network Approach To Blind Separation And Enhancement Of Images

Author:

Subject: Andrzej Cichocki Neural Network Approach To Blind Separation And Enhancement Of Images

Description: In this contribution we propose a new solution for the problem of blind separation of sources (for one dimensional signals and images) in the case that not only the waveform of sources is unknown, but also their number. For this purpose multi--layer neural networks with associated adaptive learning algorithms are developed. The primary source signals can have any non--Gaussian distribution, i.e. they can be sub--Gaussian and/or super-- Gaussian. Computer experiments are presented which demonstrate the validity and high performance of the proposed approach. 1 INTRODUCTION Blind signal processing and especially blind separation of sources is a new emerging field of research with many potential applications in science and technology [1] - [8]. Let us assume a number of independent sources are linearly mixed by unknown mixing coefficients according to the matrix equation x(t) = As(t), where s(t) = [s 1 (t); :::; s m (t)] T is a vector of unknown zero-- mean primary sources, A 2 R n2m...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1998-07-28

Pubyear: 1996

Format: ps

Identifier: http://citeseer.ist.psu.edu/140773.html

Source: http://www.open.brain.riken.go.jp/~kas/PSPAP/eusip96.ps.gz

Language: en

Relation:

Relation:

Relation:

Relation:

Rights: unrestricted

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