Transport in reservoir computing

Understand

Reservoir computing systems are constructed using a driven dynamical system in which external inputs can alter the evolving states of a system.

• These paradigms are used in information processing, machine learning, and computation.
• A fundamental question that needs to be addressed in this framework is the statistical relationship between the input and the system states.
• This paper provides conditions that guarantee the existence and uniqueness of asymptotically invariant measures for driven systems and shows that their dependence on the input process is continuous when the set of input and output processes are endowed with the Wasserstein distance.