Year |
Citation |
Score |
2020 |
Asgari H, Maybodi BM, Payvand M, Azghadi MR. Low-energy and fast spiking neural network for context-dependent learning on FPGA Ieee Transactions On Circuits and Systems Ii-Express Briefs. 1-1. DOI: 10.1109/Tcsii.2020.2968588 |
0.37 |
|
2020 |
Almasi M, Karimi G, Ranjbar M, Azghadi MR. New analogue stop-learning control module using astrocyte for neuromorphic learning Iet Circuits Devices & Systems. 14: 100-106. DOI: 10.1049/Iet-Cds.2019.0297 |
0.362 |
|
2019 |
Hashemi S, Azghadi MR, Navi K. Design and analysis of efficient QCA reversible adders The Journal of Supercomputing. 75: 2106-2125. DOI: 10.1007/S11227-018-2683-0 |
0.37 |
|
2017 |
Aghnout S, Karimi G, Azghadi MR. Modeling triplet spike-timing-dependent plasticity using memristive devices Journal of Computational Electronics. 16: 401-410. DOI: 10.1007/S10825-017-0972-0 |
0.563 |
|
2016 |
Azghadi MR, Linares-Barranco B, Abbott D, Leong PH. A Hybrid CMOS-Memristor Neuromorphic Synapse. Ieee Transactions On Biomedical Circuits and Systems. PMID 28026782 DOI: 10.1109/Tbcas.2016.2618351 |
0.573 |
|
2015 |
Azghadi MR, Moradi S, Fasnacht DB, Ozdas MS, Indiveri G. Programmable spike-timing-dependent plasticity learning circuits in neuromorphic VLSI architectures Acm Journal On Emerging Technologies in Computing Systems. 12. DOI: 10.1145/2658998 |
0.447 |
|
2014 |
Azghadi MR, Iannella N, Al-Sarawi SF, Indiveri G, Abbott D. Spike-based synaptic plasticity in silicon: Design, implementation, application, and challenges Proceedings of the Ieee. 102: 717-737. DOI: 10.1109/JPROC.2014.2314454 |
0.646 |
|
2013 |
Azghadi MR, Al-Sarawi S, Iannella N, Abbott D. A new compact analog VLSI model for Spike Timing Dependent Plasticity Ieee/Ifip International Conference On Vlsi and System-On-Chip, Vlsi-Soc. 7-12. DOI: 10.1109/VLSI-SoC.2013.6673236 |
0.643 |
|
2013 |
Azghadi MR, Al-Sarawi S, Abbott D, Iannella N. Pairing frequency experiments in visual cortex reproduced in a neuromorphic STDP circuit Proceedings of the Ieee International Conference On Electronics, Circuits, and Systems. 229-232. DOI: 10.1109/ICECS.2013.6815396 |
0.553 |
|
2012 |
Azghadi MR, Al-Sarawi S, Iannella N, Abbott D. Efficient design of triplet based Spike-Timing Dependent Plasticity Proceedings of the International Joint Conference On Neural Networks. DOI: 10.1109/IJCNN.2012.6252820 |
0.662 |
|
2011 |
Azghadi MR, Kavehei O, Al-Sarawi S, Iannella N, Abbott D. Novel VLSI implementation for triplet-based spike-timing dependent plasticity Proceedings of the 2011 7th International Conference On Intelligent Sensors, Sensor Networks and Information Processing, Issnip 2011. 158-162. DOI: 10.1109/ISSNIP.2011.6146525 |
0.667 |
|
2010 |
Navi K, Sayedsalehi S, Farazkish R, Azghadi MR. Five-input majority gate, a new device for quantum-dot cellular automata Journal of Computational and Theoretical Nanoscience. 7: 1546-1553. DOI: 10.1166/Jctn.2010.1517 |
0.375 |
|
2007 |
Azghadi MR, Kavehei O, Navi K. A novel design for quantum-dot cellular automata cells and full adders Journal of Applied Sciences. 7: 3460-3468. DOI: 10.3923/Jas.2007.3460.3468 |
0.351 |
|
Show low-probability matches. |