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...

• 第一著者: Cumbicus Jiménez, Andy Mauricio (author)
• フォーマット: bachelorThesis
• 言語: eng
• 出版事項: 2023
• 主題: Procesos Gausianos profundos; Enfermedad de Alzheimer; Electroencefalogramas; Deep Gaussian Process; Alzheimer disease; Electroencephalogram
• オンライン･アクセス: http://repositorio.yachaytech.edu.ec/handle/123456789/605