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Stochastic Hyperkernel Convolution Trains and h-Counting Processes

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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