Wavelet based detection of changes in the composition of RLC networks

Autor(es)

Paiva, H. M. ; Duarte, M. A. Q. ; Galvao, R. K. H. ; Hadjiloucas, S. ; IOP

• Tipo de documento: Artigo Científico
• Fonte: WAKE CONFERENCE 2021; v. 472, p. 6-pg., 2013-01-01.

Resumo

The current work discusses the compositional analysis of spectra that may be related to amorphous materials that lack discernible Lorentzian, Debye or Drude responses. We propose to model such response using a 3-dimensional random RLC network using a descriptor formulation which is converted into an input-output transfer function representation. A wavelet identification study of these networks is performed to infer the composition of the networks. It was concluded that wavelet filter banks enable a parsimonious representation of the dynamics in excited randomly connected RLC networks. Furthermore, chemometric classification using the proposed technique enables the discrimination of dielectric samples with different composition. The methodology is promising for the classification of amorphous dielectrics. (AU)

• Processo FAPESP: 11/13777-8 - Espectroscopia terahertz no domínio do tempo: desenvolvimento de métodos analíticos, técnicas de processamento de sinais, estudos bioquímicos e fundamentais
• Beneficiário: Celio Pasquini
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 11/17610-0 - Monitoramento e controle de sistemas dinâmicos sujeitos a falhas
• Beneficiário: Roberto Kawakami Harrop Galvão
• Modalidade de apoio: Auxílio à Pesquisa - Temático