Bioinspired Approach to Modeling Retinal Ganglion Cells Using System Identification Techniques. Vance, P. J., Das, G. P., Kerr, D., Coleman, S. A., McGinnity, T. M., Gollisch, T., & Liu, J. K. IEEE Transactions on Neural Networks and Learning Systems, 29(5):1796–1808, Institute of Electrical and Electronics Engineers (IEEE), May, 2018.
Paper doi bibtex @article{gdf7jx,
author = {Vance, Philip J. and Das, Gautham P. and Kerr, Dermot and Coleman, Sonya A. and McGinnity, T. Martin and Gollisch, Tim and Liu, Jian K.},
doi = {10.1109/tnnls.2017.2690139},
issn = {2162-2388},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
link = {https://doi.org/10.1109/TNNLS.2017.2690139},
month = {May},
number = {5},
pages = {1796–1808},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
title = {Bioinspired Approach to Modeling Retinal Ganglion Cells Using System Identification Techniques},
url = {http://dx.doi.org/10.1109/TNNLS.2017.2690139},
volume = {29},
year = {2018}
}
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