Deep Gaussian processes for the analysis of EEG signals in Alzheimer's diseases
Deep Gaussian Processes (DGPs) are hierarchically represented by a sequential composi- tion of a prior Gaussian processes and are equivalent to a multi-layer neural network (NN) of infinite width. DGPs are non-parametric statistical models and are used to characterize patterns of complex nonlinear s...
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Формат: | bachelorThesis |
Язык: | eng |
Опубликовано: |
2023
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Online-ссылка: | http://repositorio.yachaytech.edu.ec/handle/123456789/605 |
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