Defect-tolerant nanoelectronic pattern classifiers

International Journal of Circuit Theory and Applications

Volumn 35, Issue 3, 2007, Pages 239-264

  Lee, Jung Hoon ^a   Likharev, Konstantin K ^a  

^a STONY BROOK UNIVERSITY   (United States)

Author keywords

CMOL; CMOS; Defect tolerance; Hybrid circuits; Learning; Nanoelectronics; Nanowires; Neuromorphic networks; Pattern classification; Training

Indexed keywords

CIRCUIT THEORY; CMOS INTEGRATED CIRCUITS; LEARNING ALGORITHMS; NANOWIRES; PATTERN RECOGNITION; PERSONNEL TRAINING;

DEFECT TOLERANCE; HYBRID CIRCUITS; NEUROMORPHIC NETWORKS; SYNAPTIC WEIGHTS;

NEURAL NETWORKS;

EID: 34249809769     PISSN: 00989886     EISSN: 1097007X     Source Type: Journal    
DOI: 10.1002/cta.410     Document Type: Article

References (46)

1. International Technology Roadmap for Semiconductors, 2006 Edition. Available online at http//public.itrs.net/
2. Likharev KK. Electronics below 10 nm. In Nano and Giga Challenges in Microelectronics, Greer J et al. (eds). Elsevier: Amsterdam, 2003; 27-68.
3. Kuekes PJ, Snider GS, Williams RS. Crossbar nanocomputers. Scientific American 2005; 293(11):72-77.
4. DeHon A, Likharev KK. Hybrid CMOS/nanoelectronic digital circuits. Proceedings of ICCAD'05. IEEE: Piscataway, NJ, 2005; 375-382.
5. Chen A, Haddad S, Wu Y-C, Fang T-N, Lan Z, Avanzino S, Pangrle S, Buynoski M, Rathor M, Cai W, Tripsas N, Bill C, VanBuskirk M, Taguchi M. Non-volatile resistive switching for advanced memory applications. IEDM'05 Technical Digest. IEEE: Piscataway, NJ, 2005; 31.3.
6. Baek IG, Kim DC, Lee MJ, Kim H-J, Yim EK, Lee MS, Lee JE, Ahn SE, Seo S, Lee JH, Park JC, Cha YK, Park SO, Kim HS, Yoo IK, Chung U-In, Moon JT, Ryu BI. Multi-layer cross-point binary-oxide resistive memory (OxRAM) for post-NAND storage applications. IEDM'05 Technical Digest. IEEE; Piscataway, NJ, 2005; 31.4.
7. Ma LP, Xu Q, Yang Y. Organic electrical bistable devices and rewritable memory cells. Applied Physics Letters 2002; 80(16):4908-4910.
8. Bozano LD, Kean BW, Deline VR, Salem JR, Scott JC. Mechanism for bistability in organic memory elements. Applied Physics Letters 2004; 84(4):607-609.
9. Sezi R, Walter A, Engl R, Maltenberger A, Schumann J, Kund M, Dehm C. Organic materials for high-density non-volatile memory applications. IEDM'03 Technical Digest. IEEE; Piscataway, NJ, 2003; 10.2.1.
10. Lai Y-S, Tu C-H, Kwong D-L, Chen J-S. Bistable resistance switching of poly(N-vinylcarbazole) films for nonvolatile memory applications. Applied Physics Letters 2005; 87(12):122101.
11. Collier CP, Wong EW, Belohradsky M, Raymo FM, Stoddart JF, Kuekes PJ, Williams RS, Heath JR. Electronically configurable molecular-based logic gates. Science 1999; 285(5426):391-394.
12. Li C, Zhang D, Li X, Han S, Tang T, Zhou C, Fan W, Koehne J, Han J, Meyyappan M, Rawlett AM, Price DW, Tour JM. Fabrication approach for molecular memory arrays. Applied Physics Letters 2003; 82(4):645-647.
13. Wu W, Jung GY, Olynick DL, Straznicky J, Li Z, Li X, Ohlberg DAA, Chen Y, Wang S-Y, Liddle JA, Tong WM, Williams RS. One-kilobit cross-bar molecular memory circuits at 30nm half-pitch fabricated by nanoimprint lithography, Applied Physics A 2005; 80(6):1173-1178.
14. Chen Y-C, Chen F, Chen CT, Yu JY, Wu S, Lung SL, Liu R, Lu C-Y. An access-transistor-free (0T/1R) non-volatile resistance random access memory (RRAM) using a novel threshold switching, self-rectifying chalcogenide device. IEDM'03 Technical Digest. IEEE: Piscataway, NJ, U.S.A., 2003; 37.4.1.
15. Kund M, Beitel G, Pinnow C-U, Röhr T, Schumann J, Symanczyk R, Ufert K-D, Müller G. Conductive bridging RAM (CBRAM). lEDM'05 Technical Digest. IEEE: Piscataway, NJ, 2005; 31.5.
16. Likharev KK, Mayr A, Muckra I, Türel Ö. CrossNets: high-performance neuromorphic architectures for CMOL circuits. Annals of the New York Academy of Sciences 2003; 1006:146-163.
17. Fölling S, Türel Ö, Likharev KK. Single-electron latching switches as nanoscale synapses. Proceedings of the 2001 IJCNN. International Neural Network Society: Mount Royal, NY, 2001; 216-220.
18. Dresselhaus PD, Ji L, Han S, Lukens JE, Likharev KK. Measurement of single-electron lifetimes in multijunction traps. Physical Review Letters 1994; 72(20):3226-3229.
19. Ji L, Dresselhaus PD, Han SY, Lin K, Zheng W, Lukens JE. Fabrication and characterization of single-electron transistors and traps. Journal of Vacuum Science and Technology B 1994; 12(6):3619-3622.
20. Park J, Pasupathy AN, Goldsmith JI, Chang C, Yaish Y, Petta JR, Rinkoski M, Sethna JP, Abruna HD, McEuen PL, Ralph DC. Coulomb blockade and the Kondo effect in single-atom transistors. Nature 2002; 417(6890):722-725.
21. Kubatkin S, Danilov A, Hjort M, Cornil J, Bredas JL, Stuhr-Hansen N, Hedegard P, Bjornholm T. Single-electron transistor of a single organic molecule with access to several redox states, Nature 2003; 425(6959):698- 701.
22. Zhitenev NB, Jiang WR, Erbe A, Bao Z, Garfunkel E, Tennant DM, Cirelli RA. Control of topography, stress and diffusion at molecule-metal interfaces. Nanotechnology 2006; 17(5):1272-1277.
23. Strukov DB, Likharev KK. CMOL: devices, circuits, and architectures. In Introducing Molecular Electronics, Cuniberti G et al. (eds). Springer: Berlin, 2005; 447-477.
24. Strukov DB, Likharev KK. Architectures for defect-tolerant nanoelectronic crossbar memories. Journal of Nanoscience and Nanotechnology 2007; 7(1):151-167.
25. Strukov DB, Likharev KK. A reconfigurable architecture for hybrid CMOS/nanodevice circuits. Proceedings of the FPGA'06. ACM: New York, 2006; 131-140.
26. Türel Ö, Lee JH, Ma X, Likharev KK. Neuromorphic architectures for nanoelectronic circuits. International Journal of Circuit Theory and Applications 2004; 32(5):277-302.
27. Widrow B, Lehr MA. 30 years of adaptive neural networks. Proceedings of the IEEE 1990; 78(9):1415-1442.
28. Hertz J, Krogh, Palmer RG. Introduction to the Theory of Neural Computation. Perseus: Cambridge, MA, 1991.
29. Bishop CM. Neural Networks for Patter Recognition. Oxford University Press: Oxford, U.K., 1995.
30. Mountcastle VB. The Cerebral Cortex. Harvard University Press: Cambridge, MA, 1998.
31. Lee JH, Likharev KK. CrossNets as pattern classifiers. Lecture Notes in Computer Science 2005; 3512:446-454.
32. Xie Y, Jarbi MA. Analysis of the effects of quantization in multilayer neural networks using a statistical model. IEEE Transactions on Neural Networks 1992; 3(2):334-338.
33. Dündar G, Rose K. The effects of quantization on multilayer neural networks. IEEE Transactions on Neural Networks 1995; 6(6): 1446-1451.
34. Snider G, Kuekes P, Williams RS. CMOS-like logic in defective, nanoscale crossbars. Nanotechnology 2004; 15(8):881-891.
35. DeHon A, Naeimi H. Seven strategies for tolerating highly defective fabrication. IEEE Design and Test of Computers 2005; 22(4):306- 315.
36. LeCun Y, Bottou L, Bengio Y, Haffner P. Gradient-based learning applied to document recognition. Proceedings of the IEEE 1998; 86(11):2278-2324.
37. LeCun Y, Cortes C. The MNIST Database of Handwritten Characters. Available online at http://yann.lecun.com/exdb/mnist/
38. Bhattacharya U, Vijda S, Mallick A, Chaudhari BB, Belaid A. On the choice of training set, architecture and combination rule of multiple MLP classifiers for multi-resolution recognition of handwritten characters. Proceedings of the 9th International Workshop on Frontiers in Handwriting Recognition (IWFHR-9), 2004; 419-424.
39. Köksal F, Alpaydin E. Dündar G. Weight quantization for multi-layer perceptrons using soft weight sharing. Lecture Notes in Computer Science 2001; 2130:211-216.
40. Nowlan SJ, Hinton GE. Simplifying neural networks by soft weight-sharing. Neural Computation 1992; 4(4): 473-493.
41. Shoemaker PA, Carlin MJ, Shimabukuro RL. Backpropagation learning with binary quantization of weight. Neural Networks 1991; 4(2):231-241.
42. Lee JH, Likharev KK. In situ training of CMOL CrossNets. Proceedings of the WCCI/IJCNN'06, 2006; 5026-5034.
43. Kondo Y, Sawada Y. Functional abilities of a stochastic logic neural network. IEEE Transactions on Neural Networks 1992; 3(5):434-443.
44. Prechelt L. Proben1 - a set of neural network benchmark problems and benchmarking rules. Technical Report 21/94, Fakultät für Informatik, U. Karlsruhe, Karlsruhe, Germany, 1994.
45. Prechelt L. Automatic early stopping using cross validation: quantifying the criteria. Neural Networks 1998; 11(4):761-767.
46. Akkerman HB, Blom PWM, de Leeuw DM, de Boer B. Towards molecular electronics with large-area molecular junctions. Nature 2006; 441(7089):69-72.