Self-organizing maps with dynamic learning for signal reconstruction

Neural Networks

Volumn 20, Issue 2, 2007, Pages 274-284

  Cho, Jeongho ^a   Paiva, António R C ^a   Kim, Sung Phil ^a   Sanchez, Justin C ^a   Príncipe, José C ^a  

^a UNIVERSITY OF FLORIDA   (United States)

Author keywords

Brain machine interface; Self organizing map; Spike reconstruction; Vector quantization

Indexed keywords

BIOMEDICAL ENGINEERING; COMPUTER SIMULATION; DATA COMPRESSION; LEARNING SYSTEMS; SIGNAL RECONSTRUCTION; VECTOR QUANTIZATION;

BRAIN-MACHINE INTERFACE; DYNAMIC LEARNING RULES; SPIKE RECONSTRUCTION;

SELF ORGANIZING MAPS;

ARTICLE; BRAIN MACHINE INTERFACE; ENTROPY; HISTOGRAM; LEARNING; MAN MACHINE INTERACTION; NORMAL DISTRIBUTION; PRIORITY JOURNAL; SIGNAL NOISE RATIO; SIGNAL PROCESSING; SPIKE; WIRELESS COMMUNICATION;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; BRAIN; HUMANS; INFORMATION STORAGE AND RETRIEVAL; LEARNING; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); NEURONS; NONLINEAR DYNAMICS; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; RATS;

EID: 33847111116     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2006.12.002     Document Type: Article

References (21)

1. Bauer H., and Pawelzik K.R. Quantifying the neighborhood preservation of self-organizing feature maps. IEEE Transactions on Neural Networks 3 4 (1992) 570-579
2. Bezdek J.C. Pattern recongnition with Fuzzy objective function algorithms (1981), Plenum Press, New York, NY
3. Bossetti C.A., Carmena J.M., Nicolelis M.A.L., and Wolf P.D. Transmission latencies in a telemetry-linked brain-machine interface. IEEE Transactions on Biomedical Engineering 51 6 (2004) 919-924
4. Claussen J.C. Winner-relaxing self-organizing maps. Neural Computation 17 (2005) 996-1009
5. Erwin E., Obermayer K., and Schulten K. Self-organizing maps: Ordering, convergence properties and energy functions. Biological Cybernetics 67 1 (1992) 47-55
6. Gersho A., and Gray R.M. Vector quantization and signal compression (1992), Kluwer Academic Press, Springer, Boston, MA
7. Gray R.M. Vector quantization. IEEE ASSP Magazine (1984) 4-29
8. Kaski S., Honkela T., Lagus K., and Kohonen T. WEBSOM-Selforganizing maps of document collections. Neurocomputing 21 (1998) 101-117
9. Kohonen T. Self-organization and associative memory (1989), Springer-Verlag
10. Kohonen T. Self-organizing maps (1995), Springer-Verlag
11. Kohonen, T. (1997). Exploration of very large databases by self-organizing maps. In Proc. int. conf. neural networks (pp. PL1-PL6)
12. Linde Y., Buzo A., and Gray R.M. An algorithm for vector quantizer design. IEEE Transactions on Communications 28 (1980) 84-95
13. Musallam S., Corneil B.D., Greger B., Scherberger H., and Andersen R.A. Cognitive control signals for neural prosthetics. Science 305 5681 (2004) 256-262
14. Olsson, R., & Wise, K. (2005). A three-dimensional neural recording microsystem with implantable data compression circuitry. In Proc. IEEE int. solid-state circuits conf. (pp. 558-559)
15. Paiva, A.R.C., Principe, J.C., & Sanchez, J.C. (2005). Compression of spike data using the self-organizing map. In Proc. IEEE EMBS neural engineering conf
16. Salomon D. Data compression: The complete reference (2000), Springer-Verlag
17. Sayood K. Introduction to data compression (1996), Morgan Kaufmann
18. Serruya M.S., Hatsopoulos N.G., Paninski L., Fellows M.R., and Donoghue J.P. Brain-machine interfaces: Instant neural control of a movement signal. Nature 416 (2002) 141-142
19. Taylor D.M., Tillery S.I.H., and Schwartz A.B. Direct cortical control of 3d neuroprosthetic devices. Science 296 5574 (2002) 1829-1832
20. Wessberg J., Stambaugh C.R., Kralik J.D., Beck P.D., Laubach M., Chapin J.K., et al. Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 408 16 (2000) 361-365
21. Wise K.D., Anderson D.J., Hetke J.F., Kipke D.R., and Najafi K. Wireless implantable microsystems: High-density electronic interfaces to the nervous system. Proceedings of the IEEE 92 1 (2004) 76-97