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Parameter Experimental Analysis of the Reservoirs Observers using Echo State Network Approach [article]

Diana C. Roca Arroyo, Josimar E. Chire Saire
2020 arXiv   pre-print
In this work, an experimental analysis of parameters of the model Echo State Network is performed and the influence of the kind of Complex Network is explored to understand the influence on the performance  ...  Dynamical systems has a variety of applications for the new information generated during the time.  ...  For a good performance of ESN, the reservoir must satisfied a condition about his state dynamics(echo property), the state of reservoir is an echo of the history of his inputs.  ... 
arXiv:2009.13498v1 fatcat:rkxykth7djhqfe5kvry7c2drnu

A Comparative Study of Reservoir Computing for Temporal Signal Processing [article]

Alireza Goudarzi, Peter Banda, Matthew R. Lakin, Christof Teuscher, Darko Stefanovic
2014 arXiv   pre-print
A readout layer is then trained to reconstruct a target output from the reservoir's state.  ...  Here, we compare echo state networks (ESN), a popular RC architecture, with tapped-delay lines (DL) and nonlinear autoregressive exogenous (NARX) networks, which we use to model systems with limited computation  ...  Echo State Network In our ESN, the reservoir consists of a fully connected network of N nodes extended with a constant bias node b = 1.  ... 
arXiv:1401.2224v1 fatcat:xrqaesiqojaqtc2jex62zzvtci

On the Post Hoc Explainability of Optimized Self-Organizing Reservoir Network for Action Recognition

Gin Chong Lee, Chu Kiong Loo
2022 Sensors  
with the deterministic initialization of Echo State Network (ESN) input and reservoir weights, in the context of human action recognition (HAR).  ...  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  ...  Acknowledgments: The authors would like to thank the anonymous reviewer for his/her comments. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s22051905 pmid:35271052 pmcid:PMC8914683 fatcat:zh2mzzl2tbefbeqtv7kbae6xhq

A Developmental Approach to Structural Self-Organization in Reservoir Computing

Jun Yin, Yan Meng, Yaochu Jin
2012 IEEE Transactions on Autonomous Mental Development  
More specifically, a recurrent spiking neural network is adopted for building up the reservoir, whose synaptic and structural plasticity are regulated by a gene regulatory network (GRN).  ...  Reservoir computing (RC) is a computational framework for neural network based information processing. Little work, however, has been conducted on adapting the structure of the neural reservoir.  ...  ACKNOWLEDGEMENTS The authors are grateful to the anonymous reviewers and the editors for their insightful comments on an early version of the paper, which have greatly improved the quality of the paper  ... 
doi:10.1109/tamd.2012.2182765 fatcat:cp3isuziirgcfix5xzi2szbyua

Distributed Supervised Learning using Neural Networks [article]

Simone Scardapane
2016 arXiv   pre-print
We consider two different families of networks, namely echo state networks (extending the algorithms introduced in the second part), and spline adaptive filters.  ...  In this thesis, we analyze multiple distributed protocols for a large number of neural network architectures.  ...  These include random vector functional-link (RVFLs) [77, 121] , and echo state networks (ESNs) [104] .  ... 
arXiv:1607.06364v1 fatcat:plec4rmorvf7rbpviexk4pihda

Reservoir computing approaches to EEG-based detection of microsleeps [article]

Sudhanshu Ayyagari, University Of Canterbury
2017
The main motivation of this project was to develop a state-of-the-art lapse detection system by employing novel classifier schemes based on reservoir computing (RC), specifically echo state networks (ESNs  ...  real time and trigger an alert to rouse the user from an impending microsleep.  ...  Jaeger and Haass Justification for using echo state networks for microsleep detection The echo state network is a relatively new approach to designing, training, and analysis of RNNs.  ... 
doi:10.26021/1455 fatcat:7n4d765zjrhpdow66ut2klnsbq

Hydraulic-hydrologic model for the Zambezi River using satellite data and artificial intelligence techniques

José Pedro Gamito De Saldanha Calado Matos
2014
Over the ZRB, errors in the POM interpolated rainfall series were observed to be on par with those of state-of-the-art satellite rainfall estimates.  ...  In parallel, an analysis of the Soil and Water Assessment Tool (SWAT) hydrological model in its application to the ZRB has evidenced inadequacies in the source code which should be taken into account,  ...  These range from the Bayesian regularization algorithm, mentioned before, to pruning network weights (e.g. Haykin 1994), or implementing a cross-validation scheme.  ... 
doi:10.5075/epfl-thesis-6225 fatcat:bwipnhq2ibeszn5rzbz2pquxje

Hydraulic-hydrologic model for the Zambezi River using satellite data and artificial intelligence techniques

José Pedro Gamito De Saldanha Calado Matos
2015
Matos used machine-learning models in an innovative way for discharge forecast. He compared the alternative models (e.g.  ...  Over the ZRB, errors in the POM interpolated rainfall series were observed to be on par with those of state-of-the-art satellite rainfall estimates.  ...  These range from the Bayesian regularization algorithm, mentioned before, to pruning network weights (e.g. Haykin 1994), or implementing a cross-validation scheme.  ... 
doi:10.5075/epfl-lchcomm-60 fatcat:h4clh6msxvcfpmes2nntnuzeuu