Minimal Euler State Networks

The Euler State Network (EuSN) is a recently proposed Reservoir Computing (RC) model where the fixed state dynamics are obtained by discretizing an ordinary differential equation under stability and non-dissipative conditions. As a result, the model is able to effectively propagate input information over time, hugely improving the performance of RC models in tasks requiring long-term memory. Aiming at both reducing the complexity of the reservoir structure and further improving its efficiency, in this paper we propose a minimalistic EuSN architecture where the reservoir is constrained to a fixed bi-directional chain structure. We explore progressive simplifications where the recurrent and the input connections of the reservoir are fully described by a single weight value. While reducing the complexity of the base EuSN, the proposed minimal EuSN approach shows comparable performance on several tasks on time-series classification, thus offering considerable potential advantages, especially in embedded applications and physical implementations.