Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Sebastian Jenderny"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Circuit implementations of neuronal networks so far have been focusing on synaptic weight changes as network growth principles. Besides these weight changes, however, it is also useful to incorporate additional network growth principles such
Externí odkaz:
https://doaj.org/article/f09a5ae7c4e94922810924365abce90b
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers. 68:3656-3667
Hardware realizations of neuronal networks should also consider axon growth in addition to synaptic weight changes, because this accounts for an additional dynamic aspect due to the delayed signal transmission varying with the grown axon length. Our
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::740c8f4645de7ad2b34d7d9e4ee23c3b
https://doi.org/10.1109/tcsi.2021.3093172
https://doi.org/10.1109/tcsi.2021.3093172
Autor:
Sebastian Jenderny, Karlheinz Ochs
Publikováno v:
International Journal of Circuit Theory and Applications. 49:3526-3539
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0aef7dbdc1fa4d384b545a6d39aec2b8
https://doi.org/10.1002/cta.3113
https://doi.org/10.1002/cta.3113
Autor:
Sebastian Jenderny, Karlheinz Ochs
Publikováno v:
2022 IEEE Biomedical Circuits and Systems Conference (BioCAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c11be2f6d09ae1c9db4665971ffb74a
https://doi.org/10.1109/biocas54905.2022.9948613
https://doi.org/10.1109/biocas54905.2022.9948613
Autor:
Sebastian Jenderny, Karlheinz Ochs
Publikováno v:
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields. 36
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0b00cfbbfeeb5fb7c223afe16d0c3bc
https://doi.org/10.1002/jnm.3053
https://doi.org/10.1002/jnm.3053
Publikováno v:
2022 IEEE 65th International Midwest Symposium on Circuits and Systems (MWSCAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3644ae70513b411030ca0922b7b6d476
https://doi.org/10.1109/mwscas54063.2022.9859299
https://doi.org/10.1109/mwscas54063.2022.9859299
Publikováno v:
MWSCAS
A promising approach for efficiently solving NP-hard optimization problems is based on mapping the problems onto Ising machines. Oscillator-based Ising machines can be implemented by utilizing sub-harmonic injection locking, which enables binary phas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6fc9844283a443e5fd6145441009837e
https://doi.org/10.1109/mwscas47672.2021.9531734
https://doi.org/10.1109/mwscas47672.2021.9531734
Publikováno v:
MWSCAS
Circuit implementations of neuronal networks should also consider dynamic axon models, since this introduces an additional dynamic aspect due to the transmission delays depending on the axon length. In this work, we derive an electrical circuit for s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b821d0c25e6c110bca9ec3375db5a2eb
https://doi.org/10.1109/mwscas47672.2021.9531806
https://doi.org/10.1109/mwscas47672.2021.9531806
Publikováno v:
MWSCAS
The topic of synchronization has attracted a lot of interest especially because it is related to learning processes. A popular learning process is given by the Hebbian learning, which in the context of oscillatory neural networks can be interpreted a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83dc53966297da1c91893f5ea855131d
https://doi.org/10.1109/mwscas47672.2021.9531847
https://doi.org/10.1109/mwscas47672.2021.9531847
Publikováno v:
MWSCAS
Models of neuronal networks should account for axon growth in addition to dynamical synapses, because this results in a self-organized topology formation introducing an additional dynamic aspect due to the varying axonal delay. In order to bridge the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11722517876ab86cbdf49ca635830e9a
https://doi.org/10.1109/mwscas47672.2021.9531834
https://doi.org/10.1109/mwscas47672.2021.9531834