Cargando…
Classification of EEG Signals Using Neural Network for Predicting Consumer Choices
EEG, or Electroencephalogram, is an instrument that examines the brain's functions while it is executing any activity. EEG signals to aid in the identification of brain processes and movements and are thus useful in the detection of neurobiological illnesses. Pulses have a very weak magnitude a...
Autores principales: | Sheela sobana Rani, K., Pravinth Raja, S, Sinthuja, M., Vidhya Banu, B, Sapna, R., Dekeba, Kenenisa |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9328993/ https://www.ncbi.nlm.nih.gov/pubmed/35909868 http://dx.doi.org/10.1155/2022/5872401 |
Ejemplares similares
-
Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model
por: Sudhan, M. B., et al.
Publicado: (2022) -
Recognition of Consumer Preference by Analysis and Classification EEG Signals
por: Aldayel, Mashael, et al.
Publicado: (2021) -
Investigations of CNN for Medical Image Analysis for Illness Prediction
por: Nirmala, K., et al.
Publicado: (2022) -
Mechanical properties of tef starch based edible films: Development and process optimization
por: Tafa, Kenenisa Dekeba, et al.
Publicado: (2023) -
Optimization of citron peel pectin and glycerol concentration in the production of edible film using response surface methodology
por: Asfaw, Worku Abera, et al.
Publicado: (2023)