CONTINUOUS-TIME DISTRIBUTED ESTIMATION WITH ASYMMETRIC MIXING

Autor(es)

Nascimento, Vitor H. ; Sayed, Ali H. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: 2012 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP); v. N/A, p. 4-pg., 2012-01-01.

Resumo

Discrete-time mobile adaptive networks have been successfully used to model self-organization in biological networks. We recently introduced a continuous-time adaptive diffusion strategy with the goal of better modeling physical phenomena governed by continuous-time dynamics. In the present paper we extend our previous work, proposing a new continuous-time diffusion estimation strategy that allows asymmetric mixing matrices. We prove that the new algorithm is stable and has better convergence properties than stand-alone learning for the case of doubly-stochastic mixing matrices. (AU)

• Processo FAPESP: 11/06994-2 - Algoritmos de baixo custo computacional para processamento de sinais acústicos
• Beneficiário: Vitor Heloiz Nascimento
• Modalidade de apoio: Auxílio à Pesquisa - Regular