A Study on Long-Term Fluctuation Estimator in Time-Series Prediction Network
Takayuki Furuya, Hajime Kanada, Takehiko Ogawa · Transactions of the Society of Instrument and Control Engineers · 2002
In time-series data prediction, periodic and long-term components are often separately handled in a pre-devided form. We have investigated a neural network model that can identify the two parts, simultaneously. The model consists of two parts of the network arranged in the answer-in-weights structure. In this article, we study its long-term component part.