Hierarchical neural network that learns and generates time series data

Abstract

Time series data can be divided into basic strings in which components do not appear multiple times. In the previous paper, the neural network which processes the basic strings were presented. By hierarchical connection of the neural networks general time series data can be processed. The neural network shown in this paper has the function of dividing general time series data into basic string. And by using grammatical structure on hierarchical connections, learning of time series data and generation can be realized. We aim to neural model of animals acting adaptively without advanced pattern recognition ability.