| Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications N Kasabov, NM Scott, E Tu, S Marks, N Sengupta, E Capecci, M Othman, ... Neural Networks 78, 1-14, 2016 | 191 | 2016 |
| Classification and regression of spatio-temporal signals using NeuCube and its realization on SpiNNaker neuromorphic hardware J Behrenbeck, Z Tayeb, C Bhiri, C Richter, O Rhodes, N Kasabov, ... Journal of neural engineering 16 (2), 026014, 2019 | 49 | 2019 |
| Design methodology and selected applications of evolving spatio-temporal data machines in the NeuCube neuromorphic framework N Kasabov, N Scott, E Tu, S Marks, N Sengupta, E Capecci, M Othman, ... Neural Networks 78 (2016)), 1-14, 2016 | 35 | 2016 |
| Application of a brain-inspired spiking neural network architecture to odor data classification A Vanarse, JI Espinosa-Ramos, A Osseiran, A Rassau, N Kasabov Sensors 20 (10), 2756, 2020 | 26 | 2020 |
| Pulsewidth modulation-based algorithm for spike phase encoding and decoding of time-dependent analog data A Arriandiaga, E Portillo, JI Espinosa-Ramos, NK Kasabov IEEE Transactions on Neural Networks and Learning Systems 31 (10), 3920-3931, 2019 | 17 | 2019 |
| A computational model of neuroreceptor-dependent plasticity (nrdp) based on spiking neural networks JI Espinosa-Ramos, E Capecci, N Kasabov IEEE Transactions on Cognitive and Developmental Systems 11 (1), 63-72, 2017 | 13 | 2017 |
| Incorporating structural plasticity approaches in spiking neural networks for EEG modelling MMA Weerasinghe, JI Espinosa-Ramos, GY Wang, D Parry IEEE access 9, 117338-117348, 2021 | 10 | 2021 |
| Locating seismic-sense stations through genetic algorithm: genetic algorithms JI Espinosa Ramos, RA Vázquez Espinoza de los Monteros Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011 | 9 | 2011 |
| Utilizing the neuronal behavior of spiking neurons to recognize music signals based on time coding features D Shah, A Narayanan, JI Espinosa-Ramos IEEE Access 10, 37317-37329, 2022 | 8 | 2022 |
| Creation of spiking neuron models applied in pattern recognition problems JI Espinosa-Ramos, N Cruz-Cortés, RA Vazquez The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8, 2013 | 8 | 2013 |
| Machine learning with a snapshot of data: Spiking neural network ‘predicts’ reinforcement histories of pigeons' choice behavior A Plessas, JI Espinosa‐Ramos, D Parry, S Cowie, J Landon Journal of the Experimental Analysis of Behavior 117 (3), 301-319, 2022 | 7 | 2022 |
| Modelling absence epilepsy seizure data in the neucube evolving spiking neural network architecture E Capecci, JI Espinosa-Ramos, N Mammone, N Kasabov, ... 2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015 | 7 | 2015 |
| Spatiotemporal EEG dynamics of prospective memory in ageing and mild cognitive impairment M Crook-Rumsey, CJ Howard, Z Doborjeh, M Doborjeh, JIE Ramos, ... Cognitive Computation 15 (4), 1273-1299, 2023 | 6 | 2023 |
| From von Neumann Architecture and Atanasoff’s ABC to Neuromorphic Computation and Kasabov’s NeuCube. Part II: Applications M Gholami Doborjeh, Z Gholami Doborjeh, AR Gollahalli, ... Practical Issues of Intelligent Innovations, 17-36, 2018 | 4 | 2018 |
| Modelling gene interaction networks from time-series gene expression data using evolving spiking neural networks E Capecci, JL Lobo, I Laña, JI Espinosa-Ramos, N Kasabov Evolving Systems 11 (4), 599-613, 2020 | 3 | 2020 |
| From von Neumann Architecture and Atanasoffs ABC to Neuro-Morphic Computation and Kasabov’s NeuCube: Principles and Implementations N Sengupta, JIE Ramos, E Tu, S Marks, N Scott, J Weclawski, ... Learning Systems: From Theory to Practice, 1-28, 2018 | 3 | 2018 |
| A new objective function to build seismic networks using differential evolution JI Espinosa-Ramos 2012 IEEE Congress on Evolutionary Computation, 1-7, 2012 | 2 | 2012 |
| Designing spiking neural models of neurophysiological recordings using gene expression programming JI Espinosa-Ramos, RA Vazquez, N Cruz-Cortes BMC Neuroscience 14 (Suppl 1), P74, 2013 | 1 | 2013 |
| Spiking Neuron Model Approximation using GEP JI Espinosa-Ramos, NC Cortés, RA Vázquez 2013 IEEE Congress on Evolutionary Computation, 3260-3267, 2013 | 1 | 2013 |
| Performance comparison of spiking neural networks to other artificial models in predicting pigeons’ learning history from binary choices A Plessas, J Bensemann, JI Espinosa-Ramos, S Cowie, J Landon, ... | | 2024 |
Prof. Nikola Kasabov, LFIEEE, FRSNZ,...Knowledgeengineering.ai, Auckland University of Technology; IICT Bulgarian Academy of SciencesVerified email at aut.ac.nz
