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

Autor(es)

Pelegrina, Guilherme D. ^[1] ; Duarte, Leonardo T. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Estadual Campinas, Sch Appl Sci, BR-13484350 Limeira - Brazil

• Tipo de documento: Artigo Científico
• Fonte: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS; v. 65, n. 12, p. 2067-2071, DEC 2018.
• Citações Web of Science: 1

Resumo

Blind source separation (BSS) methods have been applied to deal with the lack of selectivity of ion-selective electrodes. In this brief, 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. (AU)

• Processo FAPESP: 15/16325-1 - Desenvolvimento de novos métodos de apoio à decisão multicritério utilizando técnicas avançadas de processamento de sinais
• Beneficiário: Leonardo Tomazeli Duarte
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 14/27108-9 - Métodos de otimização multiobjetivo aplicados a problemas inversos e à separação cega de fontes
• Beneficiário: Guilherme Dean Pelegrina
• Modalidade de apoio: Bolsas no Brasil - Mestrado