On the Optimum Architecture of the Biologically Inspired Hierarchical Temporal Memory Model Applied to the Hand-Written Digit Recognition

Felleman, D., van Essen, D. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex (1), 1-47.10.1093/cercor/1.1.1Search in Google Scholar

Serre, T., Oliva, A., Poggio, T. (2007). A feedforward architecture accounts for rapid categorization. In: Proc. National Academy of Sciences of the USA, Vol. 15. pp. 6424-6429.Search in Google Scholar

Lee, T. S., Mumford, D. (2003). Hierarchical Bayesian inference in visual cortex. Journal of Optical Society of America A 20(7), 1434-1448.10.1364/JOSAA.20.001434Search in Google Scholar

Dean, T. (2006). Scalable inference in hierarchical generative models. In: Proc. 9th Int. Symp. on Artificial Intelligence and mathematics. pp. 1-9.Search in Google Scholar

Hawkins, J., Blakeslee, S. (2004). On intelligence. Henry Holt and Company, New York.Search in Google Scholar

George, D., Hawkins, J. (2009). Towards a mathematical theory of cortical micro-circuits. PLoS Computational Biology 5(10). DOI 10.1371/journal.pcbi.1000532.10.1371/journal.pcbi.1000532274921819816557Search in Google Scholar

George, D., Hawkins, J. (2005). Hierarchical Bayesian model of invariant pattern recognition in the visual cortex. In: Proc. Int. Joint Conf. on Neural Networks. Montreal, Canada.Search in Google Scholar

Numenta (2007). Zeta1 algorithms reference. Document version 1.0.Search in Google Scholar

Dong, J. (2001). Statistical results of human performance on USPS database. Technical report, CEN-PARMI, Concordia University.Search in Google Scholar

Dong, J. (2005). HeroSvm 2.1. http://www.cenparmi.concordia.ca/~jdong/HeroSvm.htmlSearch in Google Scholar

Thornton, J. R., Gustafsson, T., Blumenstein, M., Hine, T. (2006). Robust character recognition using hierarchical Bayesian network. In: Proc. 19th Australian Joint Conf. on Artificial Intelligence, Hobart, Australia. pp. 1259-1264.Search in Google Scholar

Thornton, J. R., Faichney, J., Blumenstein, M., Hine, T. (2008). Character recognition using hierarchical vector quantization and temporal pooling. In: Wobcke, W., Zhang, M. (eds.) Proc 21st Australasian Joint Conf. Artificial Intelligence, Vol. Lecture Notes in Computer Science. pp. 562-572.Search in Google Scholar

Bobier, B. (2007). Hand-written digit recognition using Hierarchical Temporal Memory. http://arts.uwaterloo.ca/~cnrglab/?q=system/files/SoftComputingFinalProject.pdfSearch in Google Scholar

Numenta (2009). Numenta forum: benchmark with USPS handwritten digit dataset. http://www.numenta.com/phpBB2/viewtopic.php?t=224Search in Google Scholar

Numenta (2008). Hierarchical temporal memory, concepts, theory, and terminology. Document version 1.8.0.Search in Google Scholar

George, D. (2008). How the brain might work: a hierarchical and temporal model for learning and recognition. Ph.D. thesis, Dept. of Electrical Engineering, Stanford University, USA.Search in Google Scholar

Numenta (2009). Numenta node algorithms guide, NuPIC 1.7.Search in Google Scholar

Johnson, S. T. (1967). Hierarchical clustering schemes. Psychometrika 32, 241-254.10.1007/BF022895885234703Search in Google Scholar

Numenta (2008). Vision framework guide, NuPIC 1.6.1.Search in Google Scholar

Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA.Search in Google Scholar

Wang, C. H., Srihari, S. N. (1988). A framework for object recognition in a visually complex environment and its application to locating address blocks on mail pieces. Int. Journal of Computer Vision 2(2), 125-151.10.1007/BF00133697Search in Google Scholar

Dong, J., Krzyzak, A., Suen, C. Y. (2001). Statistical results of human performance on USPS database. Technical report, Centre of Pattern Recognition and Machine Intelligence, Concordia University.Search in Google Scholar

Seewald, A. K. (2005). Digits-a dataset for hand-written digit recognition. Technical Report TR-2005-27, OFAI, Wien.Search in Google Scholar

Hull, J. J. (1994). A database for hand-written text recognition research. IEEE Transactions on Pattern Analysis and Machine Intelligence 16, 550-554.10.1109/34.291440Search in Google Scholar

LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., Jackel, L. D. (1989). Back-propagation applied to handwritten zip code recognition. Neural Computing 1(4), 541-551.10.1162/neco.1989.1.4.541Search in Google Scholar

Ernst, M. D. (2004). Permutation methods: A basis for exact inference. Statistical Science 19(4), 676-685. DOI 10.1214/088342304000000396.10.1214/088342304000000396Search in Google Scholar

Schroeder, M. R. (1991). Fractals, chaos, power laws: minutes from an infinite paradise. W. H. Freeman, New York.10.1063/1.2810323Search in Google Scholar

Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal 27, 379-423.10.1002/j.1538-7305.1948.tb01338.xSearch in Google Scholar

Martin, K. J., Hirschberg, D. S. (1996). Small sample statistics for classification error rates II: confidence intervals and significance tests.Search in Google Scholar