| Texto completo | |
| Autor(es): |
Bordin, Claudio J., Jr.
;
de Figueredo, Caio G.
;
Bruno, Marcelo G. S.
;
IEEE
Número total de Autores: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP); v. N/A, p. 5-pg., 2022-01-01. |
| Resumo | |
This paper introduces a novel distributed diffusion algorithm for tracking the state of a dynamic system that evolves on the Stiefel manifold. To compress information exchanged between nodes, the algorithm builds a Gaussian parametric approximation to the particles that are previously projected onto the tangent space to the Stiefel manifold and mapped to real vectors. Observations from neighboring nodes are then assimilated for a general nonlinear observation model. Performance results are compared to those of competing linear diffusion Extended Kalman Filters and other particle filters. (AU) | |
| Processo FAPESP: | 18/26191-0 - Métodos Bayesianos para estimação distribuída em redes cooperativas |
| Beneficiário: | Marcelo Gomes da Silva Bruno |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |