A Multi-Objective Approach for Post-Nonlinear Source Separation and its Application to Ion-Selective Electrodes

Blind source separation (BSS) methods have been applied to deal with the lack of selectivity of ion-selective electrodes (ISE). In this paper, differently from the standard BSS solutions, which are based on the optimization of a mono-objective cost function associated with a given property of the so...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2020-02
Main Authors: Pelegrina, Guilherme Dean, Duarte, Leonardo Tomazeli
Format: Article
Language:English
Subjects:
Cost function
Electrodes
Multiple objective analysis
Optimization
Selectivity
Separation
Signal processing
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Blind source separation (BSS) methods have been applied to deal with the lack of selectivity of ion-selective electrodes (ISE). In this paper, differently from the standard BSS solutions, which are based on the optimization of a mono-objective cost function associated with a given property of the sought signals, we introduce a novel approach by relying on multi-objective optimization. Numerical experiments with actual data attested that our proposal allows the incorporation of additional information on the interference model and also provides the user a set of solutions from which he/she can select a proper one according to his/her prior knowledge on the problem.
ISSN:2331-8422
DOI:10.48550/arxiv.2002.01261