Memory and forecasting capacities of nonlinear recurrent networks

Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere

(2019) Pietro Verzelli et al.   Scientific Reports

Delay-based reservoir computing: tackling performance degradation due to system response time

(2019) Silvia Ortín et al.   OPTICS LETTERS

Tackling the Trade-Off Between Information Processing Capacity and Rate in Delay-Based Reservoir Computers

(2019) Silvia Ortín et al.   Frontiers in Physics

Asymptotic Fisher memory of randomized linear symmetric Echo State Networks

(2018) Peter Tiňo   NEUROCOMPUTING

Echo state networks are universal

(2018) Lyudmila Grigoryeva et al.   NEURAL NETWORKS

Echo State Property of Deep Reservoir Computing Networks

(2017) Claudio Gallicchio et al.   Cognitive Computation

The combination of circle topology and leaky integrator neurons remarkably improves the performance of echo state network on time series prediction

(2017) Fangzheng Xue et al.   PLoS One

Nonlinear Memory Capacity of Parallel Time-Delay Reservoir Computers in the Processing of Multidimensional Signals

(2016) Lyudmila Grigoryeva et al.   NEURAL COMPUTATION

A local Echo State Property through the largest Lyapunov exponent

(2016) Gilles Wainrib et al.   NEURAL NETWORKS

Computational analysis of memory capacity in echo state networks

(2016) Igor Farkaš et al.   NEURAL NETWORKS

Short-Term Memory Capacity in Networks via the Restricted Isometry Property

(2014) Adam S. Charles et al.   NEURAL COMPUTATION

Stochastic nonlinear time series forecasting using time-delay reservoir computers: Performance and universality

(2014) Lyudmila Grigoryeva et al.   NEURAL NETWORKS

Short term memory in input-driven linear dynamical systems

(2013) Peter Tiňo et al.   NEUROCOMPUTING

Echo State Property Linked to an Input: Exploring a Fundamental Characteristic of Recurrent Neural Networks

(2012) G. Manjunath et al.   NEURAL COMPUTATION

Re-visiting the echo state property

(2012) Izzet B. Yildiz et al.   NEURAL NETWORKS

Nonlinear System Modeling With Random Matrices: Echo State Networks Revisited

(2011) Bai Zhang et al.   IEEE Transactions on Neural Networks and Learning Systems

Minimum Complexity Echo State Network

(2010) A Rodan et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS

Memory in linear recurrent neural networks in continuous time

(2009) Michiel Hermans et al.   NEURAL NETWORKS

Memory traces in dynamical systems

(2008) S. Ganguli et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA