A tighter bound for the echo state property.

Michael Buehner, Peter Young

Author Information

PMID: 16722187 DOI: 10.1109/TNN.2006.872357

This letter provides a brief explanation of echo state networks (ESNs) and provides a rigorous bound for guaranteeing asymptotic stability of these networks. The stability bounds presented here could aid in the design of echo state networks that would be applicable to control applications where stability is required.

Algorithms

Artificial Intelligence

Information Storage and Retrieval

Neural Networks, Computer

Pattern Recognition, Automated

Systems Theory

Letter Research Support, U.S. Gov't, Non-P.H.S.

Nonlinear system modeling with random matrices: echo state networks revisited.Information processing capacity of dynamical systems.Extending stability through hierarchical clusters in echo state networks.Interpretable Design of Reservoir Computing Networks Using Realization Theory.Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks.Optimal Input Representation in Neural Systems at the Edge of Chaos.Natural quantum reservoir computing for temporal information processing.Neural networks within multi-core optic fibers.Emerging opportunities and challenges for the future of reservoir computing.Selective consistency of recurrent neural networks induced by plasticity as a mechanism of unsupervised perceptual learning.

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Open Library of Bioscience