Time Series Analysis with Three Types of Noise-Mixing Effects by Neural Network

One-dimensional convolutional neural networks are often used in time series analysis. However, when noise is mixed into the data, incorrect recognition is performed and discrimination is affected. Therefore, in this study, three types of color noise are mixed into the chaotic data and compared with the case where an autocorrelation function is used.