Utilize este identificador para referenciar este registo: https://recil.grupolusofona.pt/handle/10437/10344
Título: Energy-based acoustic localization by improved elephant herding optimization
Autores: Correia, Sérgio
Beko, Marko
Tomic, Slavisa
Cruz, Luís Alberto da Silva
Palavras-chave: ENGENHARIA ELETROTÉCNICA
ELECTROTECHNICAL ENGINEERING
ENGENHARIA ACÚSTICA
ACOUSTICAL ENGINEERING
OTIMIZAÇÃO
OPTIMIZATION
Data: 2020
Editora: IEEE Access
Relatório da Série N.º: 8
1
Resumo: The present work proposes a new approach to address the energy based acoustic localization problem. The proposed approach represents an enhanced version of evolutionary optimization based on Elephant Herding Optimization (EHO), where two major contributions are introduced. Firstly, instead of random initialization of elephant population, we exploit particularities of the problem at hand to develop an intelligent initialization scheme. More precisely, distance estimates obtained at each reference point are used to determine the regions in which a source is most likely to be located at. Secondly, rather than letting elephants to simply wander around in their search for an update in the source location, we base their motion on a local search scheme which is found on a discrete gradient method. Such a methodology significantly accelerates the convergence of the proposed algorithm, and comes at a very low computational cost, since discretization allows us to avoid the actual gradient computations. Our simulation results show that the enhanced algorithm significantly outperforms the standard EHO method for low noise and matches its performance for high noise, in terms of localization accuracy. Moreover, they show that the proposed enhanced version requires significantly less number of iterations to converge.
Descrição: IEEE Access
URI: http://hdl.handle.net/10437/10344
Aparece nas colecções:Artigos de Revistas Internacionais com Arbitragem Científica (Movlab)

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