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Cited by 8
Liquid State Machine Built of Hodgkin–Huxley Neurons

2007 International Joint Conference on Neural Networks
Antonio Oliveri, Riccardo Rizzo, Antonio Chella
https://doi.org/10.1109/IJCNN.2007.4371170
Conference  (2007), p. 1441
Brain stem – from general view to computational model based on switchboard rules of operation
Włodzisław Duch, Dariusz Mikołajewski
https://doi.org/10.1515/bams-2019-0059
Journal  Bio-Algorithms and Med-Systems Volume 16, Issue 1 (2020)
Electrical parameters influence on the dynamics of the Hodgkin–Huxley liquid state machine
Grzegorz M. Wojcik
https://doi.org/10.1016/j.neucom.2011.10.007
Journal  Neurocomputing Volume 79 (2012), p. 68
Neuromorphic Computing for Interactive Robotics: A Systematic Review
Muhammad Aitsam, Sergio Davies, Alessandro Di Nuovo
https://doi.org/10.1109/ACCESS.2022.3219440
Journal  IEEE Access Volume 10 (2022), p. 122261
Neuroplasticity in rehabilitation after central nervous system damages – computational models
Emilia Mikołajewska, Dariusz Mikołajewski
https://doi.org/10.2478/rehab-2013-0029
Journal  Advances in Rehabilitation Volume 26, Issue 1 (2012), p. 51
Object Tracking in Satellite Videos by Fusing the Kernel Correlation Filter and the Three-Frame-Difference Algorithm
Bo Du, Yujia Sun, Shihan Cai, Chen Wu, Qian Du
https://doi.org/10.1109/LGRS.2017.2776899
Journal  IEEE Geoscience and Remote Sensing Letters Volume 15, Issue 2 (2018), p. 168
Self-organising criticality in the simulated models of the rat cortical microcircuits
Grzegorz M. Wojcik
https://doi.org/10.1016/j.neucom.2011.10.004
Journal  Neurocomputing Volume 79 (2012), p. 61
Time-Varying Signals Classification Using a Liquid State Machine
Antonio Chella, Riccardo Rizzo
https://doi.org/10.1007/1-4020-3432-6_16
Book  (2005), p. 133


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