Reservoir computing is a machine learning method that is closely linked to dynamical
systems theory. This connection is highlighted in a brief introduction to the general concept …

Recently, with the emergence of ChatGPT, the field of artificial intelligence has garnered
widespread attention from various sectors of society. Reservoir Computing (RC) is a …

Task specific hyperparameter tuning in reservoir computing is an open issue, and is of
particular relevance for hardware implemented reservoirs. We investigate the influence of …

Anticipating price crises in the market of agri-commodities is critical to guarantee both the
sustainability of the food system and to ensure food security. However, this is not an easy …

Reservoir computing (RC) is a simple and efficient model-free framework for forecasting the
behavior of nonlinear dynamical systems from data. Here, we show that there exist …

Although the attention mechanism in transformers has proven successful in image-text
retrieval tasks, most transformer models suffer from a large number of parameters. Inspired …

The reservoir computing (RC) system, known for its ability to seamlessly integrate memory
and computing functions, is considered as a promising solution to meet the high demands …

Human–machine interaction (HMI) technology has undergone significant advancements in
recent years, enabling seamless communication between humans and machines. Its …

Reservoir computing is a machine learning paradigm that uses a structure called a reservoir,
which has nonlinearities and short-term memory. In recent years, reservoir computing has …

We show that many delay-based reservoir computers considered in the literature can be
characterized by a universal master memory function (MMF). Once computed for two …