Optimal nonlinear information processing capacity in delay-based reservoir computers.

ABSTRACT: Reservoir computing is a recently introduced brain-inspired machine learning paradigm capable of excellent performances in the processing of empirical data. We focus in a particular kind of time-delay based reservoir computers that have been physically implemented using optical and electronic systems and have shown unprecedented data processing rates. Reservoir computing is well-known for the ease of the associated training scheme but also for the problematic sensitivity of its performance to architecture parameters. This article addresses the reservoir design problem, which remains the biggest challenge in the applicability of this information processing scheme. More specifically, we use the information available regarding the optimal reservoir working regimes to construct a functional li

SUBMITTER: Grigoryeva L 

PROVIDER: S-EPMC4566100 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature