Reservoir computing (RC) refers to a new class of state-space models with a fixed state
transition structure (the reservoir) and an adaptable readout form the state space. The …

Abstract Echo State Networks, ESNs, are standardly composed of additive units undergoing
sigmoid function activation. They consist of a randomly recurrent neuronal infra-structure …

Echo State Networks (ESNs) constitute an emerging approach for efficiently modeling
Recurrent Neural Networks (RNNs). In this paper we investigate some of the main aspects …

A new class of state-space models, reservoir models, with a fixed state transition structure
(the “reservoir”) and an adaptable readout from the state space, has recently emerged as a …

Reservoir computing became very popular due to its potential for efficient design of recurrent
neural networks, exploiting the computational properties of the reservoir structure. Various …

This article develops approaches to generate dynamical reservoirs of echo state networks
with desired properties reducing the amount of randomness. It is possible to create weight …

Underwater acoustic (UWA) communications have been widely used but greatly impaired
due to the complicated nature of the underwater environment. In order to improve UWA …

This paper investigates the interaction between the driving output feedback and the internal
reservoir dynamics in echo state networks (ESNs). The interplay is studied experimentally …

Echo State Networks ESNs are specific kind of recurrent networks providing a black box
modeling of dynamic non-linear problems. Their architecture is distinguished by a randomly …

In this paper, an integrated data validation/reconstruction and fault diagnosis approach is
proposed for critical infrastructure systems. The proposed methodology is implemented in a …