  Echo State Networks are efficient time-series predictors, which highly depend
on the value of the spectral radius of the reservoir connectivity matrix. Based
on recent results on the mean field theory of driven random recurrent neural
networks, enabling the computation of the largest Lyapunov exponent of an ESN,
we develop a cheap algorithm to establish a local and operational version of
the Echo State Property.
