On a Direct and Parallel Denoising Autoencoder and Its Evaluation

Abstract

Denoising problems from time-series signals are important to get reliable data in the various fields (e.g., engineering, medical science and so on). The general methods for denoising are required knowledge about frequency bands causing noises. In contrast, a denoising autoencoder proposed in recent years is not required it. In this study, we propose a direct and parallel denoising autoencoder for high quality denoising algorithm. Here we describe proposed method and show its evaluation.