International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 129 - Number 16 |
Year of Publication: 2015 |
Authors: Fatemeh Asgari, Ali Salehi |
10.5120/ijca2015906880 |
Fatemeh Asgari, Ali Salehi . The biologically inspired Hierarchical Temporal Memory Model for Farsi Handwritten Digit and Letter Recognition. International Journal of Computer Applications. 129, 16 ( November 2015), 6-11. DOI=10.5120/ijca2015906880
It is herein proposed a handwritten digit recognition system which biologically inspired of the large-scale structure of the mammalian neocortex. Hierarchical Temporal Memory (HTM) is a memory-prediction network model that takes advantage of the Bayesian belief propagation and revision techniques. In this article a study has been conducted to train a HTM network to recognize handwritten digits and letters taken from the well-known Hoda dataset for Farsi handwritten digit. Results presented in this paper show good performance and generalization capacity of the proposed network for a real-world big dataset.