In-ear EEG based attention state classification using echo state network
It is important to maintain attention when carrying out significant daily-life tasks that require
high levels of safety and efficiency. Since degradation of attention can sometimes have dire …
high levels of safety and efficiency. Since degradation of attention can sometimes have dire …
Deep photonic reservoir computer for speech recognition
Speech recognition is a critical task in the field of artificial intelligence (AI) and has
witnessed remarkable advancements thanks to large and complex neural networks, whose …
witnessed remarkable advancements thanks to large and complex neural networks, whose …
Using echo state networks for classification: A case study in Parkinson's disease diagnosis
Despite having notable advantages over established machine learning methods for time
series analysis, reservoir computing methods, such as echo state networks (ESNs), have yet …
series analysis, reservoir computing methods, such as echo state networks (ESNs), have yet …
Multilayer time delay reservoir with double feedback loops for time series forecasting task
M You, F Li, J Xi, G Wang, B Du - Applied Soft Computing, 2023 - Elsevier
Abstract Time Delay Reservoir (TDR) is a special single-node reservoir to process time
dependent signals simply and efficiently. It has good performance on time series forecasting …
dependent signals simply and efficiently. It has good performance on time series forecasting …
Input-to-state representation in linear reservoirs dynamics
Reservoir computing is a popular approach to design recurrent neural networks, due to its
training simplicity and approximation performance. The recurrent part of these networks is …
training simplicity and approximation performance. The recurrent part of these networks is …
A novel method for lake level prediction: deep echo state network
Accurately prediction of lake level fluctuations is essential for water resources planning and
management. In the present study, the potential of a novel method, deep echo state network …
management. In the present study, the potential of a novel method, deep echo state network …
Decoding electroencephalographic signals for direction in brain-computer interface using echo state network and Gaussian readouts
HH Kim, J Jeong - Computers in biology and medicine, 2019 - Elsevier
Background Noninvasive brain-computer interfaces (BCI) for movement control via an
electroencephalogram (EEG) have been extensively investigated. However, most previous …
electroencephalogram (EEG) have been extensively investigated. However, most previous …
Features extraction from human eye movements via echo state network
The paper develops a procedure for features extraction from eye movement's time series
aimed at age-related classification of humans. It exploits the properties of the echo state …
aimed at age-related classification of humans. It exploits the properties of the echo state …
An intelligent interconnected network with multiple reservoir computing
X Yao, Z Wang - Applied Soft Computing, 2019 - Elsevier
In this paper, considering the decomposition and composition mechanism of the traditional
reservoir, an intelligent interconnected network with multiple reservoir computing in series …
reservoir, an intelligent interconnected network with multiple reservoir computing in series …
Classification via tensor decompositions of echo state networks
A Prater - 2017 IEEE Symposium Series on Computational …, 2017 - ieeexplore.ieee.org
Typically when performing supervised classification tasks on data processed in an echo
state network, the entire collection of hidden layer node states from the training dataset is …
state network, the entire collection of hidden layer node states from the training dataset is …