Image Object Recognition Based on Biologically Inspired Hierarchical Temporal Memory Model and Its Application to the USPS Database
Ivan Bajla · 2009
In the paper we describe basic functions of a Hierarchical Temporal Memory (HTM) based on a novel biologically inspired network model of the overall large-scale structure of human neocortex. It appeared in a form of research release of the system NuPIC (Numenta Platform for Intelligent Computing) in 2007. In the design of the HTM, hierarchical structure and spatio-temporal relations serve for generation of invariant representations of the outer world (e.g. world of visual patterns), similar to those in human neocortex. There are several open issues for a research into HTM, in particular those applied to pattern recognition tasks. In the paper we report our results of the HTM architecture design and optimization of the network parameters for the task of recognition of the handwritten digits from the well benchmarked USPS database.