NEUROMORFNO RAČUNARSTVO – IMPULSNE NEURONSKE MREŽE
Ključne reči:
Neuromorfno računarstvo, Impulsne neuronske mreže, LIF model
Apstrakt
Neuromorfno računarstvo je oblast u razvoju koja nalazi sve veću primenu. U ovom radu biće ukratko prikazani principi funkcionisanja neuromorfnog računarstva, kao i rezultati implementacije jedne Spiking (impulsne) neuronske mreže u kojoj su sinapse obučene da svoje težine prilagode odgovarajućim ulazima.
Reference
[1] W. Gerstner, W.M. Kistler, “Spiking neuron models: Single neurons, populations, plasticity”, New York, US: Cambridge University Press, 2002. isbn: 978-0-521-81384-6. doi: 10.1017/CBO9780511815706.
[2] A.L. Hodgkin, A.F. Huxley, “A quantitative description of membrane current and its application to conduction and excitation in nerve,” J. Physiol., Vol. 117, no. 4, pp. 500–544, Aug. 1952. [Online]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1392413/
[3] E. Izhikevich, “Simple model of spiking neurons”, IEEE Trans. Neural Netw., vol. 14, no. 6, pp. 1569–1572, Nov. 2003. doi: 10.1109/TNN.2003.820440.
[4] N. Caporale, Y. Dan, “Spike timing-dependent plasticity: a Hebbian learning rule,” eng, Annual Review of Neuroscience, Vol. 31, pp. 25–46, 2008. doi: 10.1146/ annurev.neuro.31.060407.125639.
[2] A.L. Hodgkin, A.F. Huxley, “A quantitative description of membrane current and its application to conduction and excitation in nerve,” J. Physiol., Vol. 117, no. 4, pp. 500–544, Aug. 1952. [Online]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1392413/
[3] E. Izhikevich, “Simple model of spiking neurons”, IEEE Trans. Neural Netw., vol. 14, no. 6, pp. 1569–1572, Nov. 2003. doi: 10.1109/TNN.2003.820440.
[4] N. Caporale, Y. Dan, “Spike timing-dependent plasticity: a Hebbian learning rule,” eng, Annual Review of Neuroscience, Vol. 31, pp. 25–46, 2008. doi: 10.1146/ annurev.neuro.31.060407.125639.
Objavljeno
2025-04-04
Sekcija
Elektrotehničko i računarsko inženjerstvo
