Sparse representations of high dimensional neural data

Conventional Vector Autoregressive (VAR) modelling methods applied to high dimensional neural time series data result in noisy solutions that are dense or have a large number of spurious coefficients. This reduces the speed and accuracy of auxiliary computations downstream and inflates the time requ...

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Detalles Bibliográficos
Autores principales: Mody, Sandeep K., Rangarajan, Govindan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068763/
https://www.ncbi.nlm.nih.gov/pubmed/35508638
http://dx.doi.org/10.1038/s41598-022-10459-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068763/
https://www.ncbi.nlm.nih.gov/pubmed/35508638
http://dx.doi.org/10.1038/s41598-022-10459-7

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