عنوان انگلیسی مقاله:
Application of multi-objective optimization to blind source separation
ترجمه فارسی عنوان مقاله:
استفاده از بهینه سازی چند هدفه برای جداسازی منبع کور
Sciencedirect - Elsevier - Expert Systems With Applications, 131 (2019) 60-70: doi:10:1016/j:eswa:2019:04:041
Guilherme Dean Pelegrina a , ∗, Romis Attux b , Leonardo Tomazeli Duarte a
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.
Keywords: Blind source separation | Multi-objective optimization | Evolutionary algorithms