Abstract: A device may receive real network data associated with a network, and may receive a random latent vector and a random process sample. The device may utilize the random latent vector with a generative adversarial network (GAN) model to generate synthetic network data, and may train the GAN model with the real network data and the synthetic network data to generate a trained GAN model. The device may utilize the random process sample with a random process to generate simulated network data, and may apply weights to the real network data, the synthetic network data, and the simulated network data to generate weighted real network data, weighted synthetic network data, and weighted simulated network data. The device may combine the weighted real network data, the weighted synthetic network data, and the weighted simulated network data to generate interpolated network data, and may perform actions based on the interpolated network data.

Abstract: A method and an electronic device for measuring blood pressure are provided. The method includes illuminating, by a PPG sensor included in the electronic device, skin of a user and measuring a PPG signal based on an illumination absorption by the skin. Further, the method also includes extracting, by the electronic device, a plurality of parameters from the PPG signal, wherein the parameters may comprise PPG features, Heart Rate Variability (HRV) features, Acceleration Plethysmograph (APG) features, and non-linear features. The method also includes estimating, by the electronic device, the BP based on the extracted plurality of parameters.

Abstract: A method and an electronic device for measuring blood pressure are provided. The method includes illuminating, by a PPG sensor included in the electronic device, skin of a user and measuring a PPG signal based on an illumination absorption by the skin. Further, the method also includes extracting, by the electronic device, a plurality of parameters from the PPG signal, wherein the parameters may comprise PPG features, Heart Rate Variability (HRV) features, Acceleration Plethysmograph (APG) features, and non-linear features. The method also includes estimating, by the electronic device, the BP based on the extracted plurality of parameters.