Variability-tolerant Convolutional Neural Network for Pattern Recognition applications based on OxRAM synapses

Technical Digest - International Electron Devices Meeting, IEDM

Volumn 2015-February, Issue February, 2015, Pages 28.4.1-28.4.4

  Garbin, D ^a,c   Bichler, O ^b   Vianello, E ^a   Rafhay, Q ^c   Gamrat, C ^b   Perniola, L ^a   Ghibaudo, G ^c   DeSalvo, B ^a  

^a CEA GRENOBLE   (France)

^b DIF   (France)

^c IMEP LAHC   (France)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATION PROGRAMS; CONVOLUTION; CONVOLUTIONAL NEURAL NETWORKS; ELECTRON DEVICES; HAFNIUM OXIDES; MAMMALS;

COMMERCIAL PRODUCTS; HARDWARE IMPLEMENTATIONS; MAMMALIAN VISUAL CORTEX; SOFTWARE IMPLEMENTATION; STATE OF THE ART; THEORETICAL STUDY; VARIABILITY TOLERANT; VISUAL PATTERN RECOGNITION;

PATTERN RECOGNITION;

EID: 84938273743     PISSN: 01631918     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEDM.2014.7047126     Document Type: Conference Paper

References (18)

1. LeCun et al., Proc. IEEE, vol.86, no.11, pp.2278, 2324, 1998.
2. Camuñas-Mesa et al., IEEE J. Solid-State Circuit vol.47, no.2, pp.504, 517, 2012.
3. Goux et al., VLSIT, pp. 159, 160, 2012.
4. Kim Y.-B. et al., VLSIT, pp. 52, 53, 2011.
5. Diokh et al., IRPS, pp. 5E.4.1, 5E.4.4, 2013.
6. Fantini et al., IMW, pp.30, 33, 2013.
7. Benoist et al., IRPS, pp. 2E.6.1, 2E.6.5, 2014.
8. Guan et al., IEEE Trans. ED, vol.59, no.4, pp.1172, 1182, 2012.
9. Ielmini et al, IEEE Trans.ED, vol.58, no.10, pp.3246, 3253, 2011.
10. Wong et al., Proc. IEEE, vol.100, no.6, pp. 1951-1970, 2012.
11. Bichler et al., NANOARCH, pp. 7, 12, 2013.
12. Suri et al., IEDM, pp. 10.3.1, 10.3.4, 2012.
13. Kuzum et al., IEDM, pp. 30.3.1, 30.3.4, 2011.
14. Suri et al., IEDM, pp. 4.4.1, 4.4.4, 2011.
15. Hubel and Wiesel, J. Physiology, 195 (1), pp. 215, 243, 1968.
16. LeCun et al., http://yann.lecun.com/exdb/mnist/.
17. Simard et al., ICDAR, pp. 958, 963, 2003.
18. Perez-Carrasco et al., TPAMI, vol.35, no.11, pp.2706, 2719, 2013