| Texto completo | |
| Autor(es): |
Atto, Abdourrahmane Mahamane
;
Vidakovic, Brani
;
Pinheiro, Aluisio
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | IEEE ACCESS; v. 11, p. 9-pg., 2023-01-01. |
| Resumo | |
The paper presents two new families of stochastic processes called hyperkernel convolution train and h-counting processes. These models generalize respectively the spike train and counting process models. The convolution train model is designed to encompass both continuous and singular spiking activities. The h-counting process can be used to model counting phenomena for which the increments are not necessarily instantaneous. This h-counting model can also be used to represent uncertainties on the exact locations of state transitions of a standard discrete event system. The paper also highlights some statistical properties of the provided convolution train model, in addition to a framework based on wavelet packets for simulating or learning such a process from multiple observations of disturbed input trains. (AU) | |
| Processo FAPESP: | 18/04654-9 - Séries temporais, ondaletas e dados de alta dimensão |
| Beneficiário: | Pedro Alberto Morettin |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |