Results 11 to 20 of about 3,514 (178)
DeePr-ESN: A deep projection-encoding echo-state network
Information Sciences, 2020 Abstract As a recurrent neural network that requires no training, the reservoir computing (RC) model has attracted widespread attention in the last decade, especially in the context of time series prediction. However, most time series have a multiscale structure, which a single-hidden-layer RC model may have difficulty capturing.
Qianli Ma +2 more
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An internet traffic classification method based on echo state network and improved salp swarm algorithm [PDF]
PeerJ Computer Science, 2022 Internet traffic classification is fundamental to network monitoring, service quality and security. In this paper, we propose an internet traffic classification method based on the Echo State Network (ESN).
Meijia Zhang +4 more
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Fuzzy-Weighted Echo State Networks
Frontiers in Energy Research, 2022 A novel echo state network (ESN), referred to as a fuzzy-weighted echo state network (FWESN), is proposed by using the structural information of data sets to improve the performance of the classical ESN. The information is incorporated into the classical
Zhao Yao, Zhao Yao, Yingshun Li
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The combination of circle topology and leaky integrator neurons remarkably improves the performance of echo state network on time series prediction. [PDF]
PLoS ONE, 2017 Recently, echo state network (ESN) has attracted a great deal of attention due to its high accuracy and efficient learning performance. Compared with the traditional random structure and classical sigmoid units, simple circle topology and leaky ...
Fangzheng Xue, Qian Li, Xiumin Li
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Grey Wolf Optimization–Based Deep Echo State Network for Time Series Prediction
Frontiers in Energy Research, 2022 The Echo State Network (ESN) is a unique type of recurrent neural network. It is built atop a reservoir, which is a sparse, random, and enormous hidden infrastructure.
Xiaojuan Chen, Haiyang Zhang
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IEEE Access, 2023 The echo state network (ESN) is a cutting-edge reservoir computing technique designed to handle time-dependent data, making it highly effective for addressing time series prediction tasks.
Zohaib Ahmad +4 more
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On the Post Hoc Explainability of Optimized Self-Organizing Reservoir Network for Action Recognition
Sensors, 2022 This work proposes a novel unsupervised self-organizing network, called the Self-Organizing Convolutional Echo State Network (SO-ConvESN), for learning node centroids and interconnectivity maps compatible with the deterministic initialization of Echo ...
Gin Chong Lee, Chu Kiong Loo
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Control-aware echo state networks (Ca-ESN) for the suppression of extreme events
, 2023 Extreme event are sudden large-amplitude changes in the state or observables of chaotic nonlinear systems, which characterize many scientific phenomena. Because of their violent nature, extreme events typically have adverse consequences, which call for methods to prevent the events from happening. In this work, we introduce the control-aware echo state
Racca, Alberto, Magri, Luca
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IEEE Access, 2022 The echo state network (ESN) is a representative model for reservoir computing, which has been mainly used for temporal pattern recognition. Recent studies have shown that multi-reservoir ESN models constructed with multiple reservoirs can enhance the ...
Takanori Akiyama, Gouhei Tanaka
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Statistical Analysis on Random Matrices of Echo State Network in PEMFC System’s Lifetime Prediction
Applied Sciences, 2022 The data-driven method of echo state network (ESN) has been successfully used in the proton exchange membrane fuel cell (PEMFC) system’s lifetime prediction area.
Zhiguang Hua +3 more
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