Cited by 949Neural Networks and Reservoir ComputingNeural Networks and ApplicationsAdvanced Memory and Neural Computing

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Optimization and applications of echo state networks with leaky- integrator neurons

Jaeger, Herbert, Lukoševičius, Mantas, Popovici, Dan, Siewert, Udo·2007·Neural Networks

DOI 10.1016/j.neunet.2007.04.016

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Abstract

Standard echo state networks (ESNs) are built from simple additive units with a sigmoid activation function. Here we investigate ESNs whose reservoir units are leaky integrator units. Units of this type have individual state dynamics, which can be exploited in various ways to accommodate the network to the temporal characteristics of a learning task. We present stability conditions, introduce and investigate a stochastic gradient descent method for the optimization of the global learning parameters (input and output feedback scalings, leaking rate, spectral radius) and demonstrate the usefulness of leaky-integrator ESNs for (i) learning very slow dynamic systems and replaying the learnt system at different speeds, (ii) classifying relatively slow and noisy time series (the Japanese Vowel dataset--here we obtain a zero test error rate), and (iii) recognizing strongly time-warped dynamic patterns.

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ВЛИЯНИЕ СТАТИСТИКИ ИНИЦИАЛИЗАЦИЙ НА ТОЧНОСТЬ РЕЗЕРВУАРНЫХ ВЫЧИСЛЕНИЙ
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Authors: Jaeger, H., Lukoševičius, M., Popovici, D., & Siewert, U.
Affiliations: Constructor University (DE)
Planet (DE)
Corresponding author: Jaeger, Herbert
ORCID: Jaeger, Herbert
Lukoševičius, Mantas
Venue: Neural Networks
Publisher: Elsevier BV
Published: 2007-04
Volume: 20
Issue: 3
Pages: 335-352
ISSN: 0893-6080 (ISSN-L)
DOI: 10.1016/j.neunet.2007.04.016
OpenAlex: W2001263627
Semantic Scholar: 370984d3910e61d41ee8318714cd610b689de726
Cited by: 948
References: 32
Citations by year: 2026: 61 · 2025: 87 · 2024: 90 · 2023: 65 · 2022: 71 · 2021: 68 · 2020: 68 · 2019: 81 · 2018: 51 · 2017: 38 · 2016: 44 · 2015: 33 · 2014: 37 · 2013: 28 · 2012: 42
FWCI: 24.86
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Neural Networks (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Reservoir Computing
Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
Keywords: echo state networks, reservoir computing, stability conditions, stochastic gradient descent, spectral radius, time series classification, time warping
MeSH terms: Animals, Feedback, Humans, Learning, Models, Neurological, Nerve Net, Neurons, Stochastic Processes, Neural Networks, Computer, Nonlinear Dynamics, Recognition, Psychology

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Optimization and applications of echo state networks with leaky- integrator neurons

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