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pro vyhledávání: '"Hajar Asgari"'
Neuromorphic engineers develop event-based spiking neural networks (SNNs) in hardware. These SNNs closer resemble the dynamics of biological neurons than conventional artificial neural networks and achieve higher efficiency thanks to the event-based,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee5b17413009ab0f0372334f3996ac73
https://www.zora.uzh.ch/id/eprint/200376/
https://www.zora.uzh.ch/id/eprint/200376/
Supervised, unsupervised, and reinforcement learning (RL) mechanisms are known as the most powerful learning paradigms empowering neuromorphic systems. These systems typically take advantage of unsupervised learning because they can learn the distrib
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f3ab16d1ed8031761ee99c870fa8dd8
https://www.zora.uzh.ch/id/eprint/200375/
https://www.zora.uzh.ch/id/eprint/200375/
Publikováno v:
AICAS
Highly efficient performance-resources trade-off of the biological brain is a motivation for research on neuromorphic computing. Neuromorphic engineers develop event-based spiking neural networks (SNNs) in hardware. Learning in SNNs is a challenging
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30ace2444a7aa1acde84e43f61ea2a5a
https://www.zora.uzh.ch/id/eprint/188460/
https://www.zora.uzh.ch/id/eprint/188460/
Spiking neural networks (SNNs) can achieve lower latency and higher efficiency compared with traditional neural networks if they are implemented in dedicated neuromorphic hardware. In both biological and artificial spiking neuronal systems, synaptic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce3d701dd74edb967b2fd303d2261af1
https://www.zora.uzh.ch/id/eprint/200379/
https://www.zora.uzh.ch/id/eprint/200379/
Publikováno v:
Procedia Technology. 17:736-741
Recently the Hopfield Neural Network (HNN) is employed as an optimization tool to solve shortest path problem in communication networks. The hardware implementation of digital Hopfield neural network is an important issue that is considered in this p
Autor:
Hajar Asgari, Yousef S. Kavian
Publikováno v:
Neural Network World. 24:211-230
The shortest path problem is an important issue in communication networks which is used by many practical routing protocols. The aim of this paper is to present an intelligent model based on Hopfield neural networks (HNNs) for solving shortest path p