Reservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into higher dimensional computational spaces through the dynamics of …

Dec 12, 2024 · In this chapter, I introduce the basic concepts of reservoir computing. Moreover, I present some important physical implementations coming from electronics, photonics, …

Oct 23, 2025 · Next-gen reservoir computing represents a thrilling evolution in how we approach computation and artificial intelligence. By moving beyond static, randomly initialized networks …

Reservoir computing (RC) is defined as a machine learning paradigm that processes information from dynamical systems using observed time series data, requiring minimal training datasets …

Dec 16, 2025 · An analog reservoir computer chip predicts chaotic systems with low power, enabling real-time learning on wearables and edge devices.

Reviewing the current state of the art and providing a concise guide to the field, this book introduces readers to its basic concepts, theory, techniques, physical implementations and …

Mar 6, 2024 · Reservoir computing originates in the early 2000s, the core idea being to utilize dynamical systems as reservoirs (nonlinear generalizations of standard bases) to adaptively …

The power of RC stems from the fact that, in theory, any dynamical system satisfying the two properties can be used as a reservoir: even a bucket of water that performs computations …

Mar 18, 2024 · Reservoir computing, a form of artificial intelligence, relies on recurrent neural networks that mimic the information storage and processing mechanisms of the human brain.

May 9, 2024 · Reservoir computing is an unconventional computing paradigm that uses system complexity and dynamics as a computational medium. Currently, it is the leading …