| Author(s): |
Nascimento, Vitor H.
;
Sayed, Ali H.
;
IEEE
Total Authors: 3
|
| Document type: | Journal article |
| Source: | 2012 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP); v. N/A, p. 4-pg., 2012-01-01. |
| Abstract | |
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) | |
| FAPESP's process: | 11/06994-2 - Low-cost algorithms for acoustic signal processing |
| Grantee: | Vitor Heloiz Nascimento |
| Support Opportunities: | Regular Research Grants |