Optimizing Memory in Reservoir Computers
Abstract
A reservoir computer is a way of using a high dimensional dynamical system for computation. One way to construct a reservoir computer is by connecting a set of nonlinear nodes into a network. Because the network creates feedback between nodes, the reservoir computer has memory. If the reservoir computer is to respond to an input signal in a consistent way (a necessary condition for computation), the memory must be fading; that is, the influence of the initial conditions fades over time. How long this memory lasts is important for determining how well the reservoir computer can solve a particular problem. In this paper I describe ways to vary the length of the fading memory in reservoir computers. Tuning the memory can be important to achieve optimal results in some problems; too much or too little memory degrades the accuracy of the computation.
Keywords
Cite
@article{arxiv.2201.01605,
title = {Optimizing Memory in Reservoir Computers},
author = {Thomas L. Carroll},
journal= {arXiv preprint arXiv:2201.01605},
year = {2022}
}