| Full text | |
| Author(s): |
Total Authors: 3
|
| Affiliation: | [1] Univ Estadual Campinas, Sch Appl Sci, 1300 Pedro Zaccaria St, BR-13484350 Limeira - Brazil
[2] Univ Estadual Campinas, Sch Elect & Comp Engn, 400 Albert Einstein Ave, BR-13083852 Campinas, SP - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | EXPERT SYSTEMS WITH APPLICATIONS; v. 131, p. 60-70, OCT 1 2019. |
| Web of Science Citations: | 0 |
| Abstract | |
Several problems in signal processing are addressed by expert systems which take into account a set of priors on the sought signals and systems. For instance, blind source separation is often tackled by means of a mono-objective formulation which relies on a separation criterion associated with a given property of the sought signals (sources). However, in many practical situations, there are more than one property to be exploited and, as a consequence, a set of separation criteria may be used to recover the original signals. In this context, this paper addresses the separation problem by means of an approach based on multi-objective optimization. Differently from the existing methods, which provide only one estimate for the original signals, our proposal leads to a set of solutions that can be utilized by the system user to take his/her decision. Results obtained through numerical experiments over a set of biomedical signals highlight the viability of the proposed approach, which provides estimations closer to the mean squared error solutions compared to the ones achieved via a mono-objective formulation. Moreover, since our proposal is quite general, this work also contributes to encourage future researches to develop expert systems that exploit the multi-objective formulation in different source separation problems. (C) 2019 Elsevier Ltd. All rights reserved. (AU) | |
| FAPESP's process: | 14/27108-9 - Multiobjective optimization method for inverse problems and blind source separation |
| Grantee: | Guilherme Dean Pelegrina |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 15/16325-1 - Novel methods in multicreria decision analysis by means of advanced signal processing techniques |
| Grantee: | Leonardo Tomazeli Duarte |
| Support Opportunities: | Regular Research Grants |