Described is a system for object identification using sparse associative memory. In operation, the system converts signature data regarding an object into a set of binary signals representing activations in a layer of input neurons. The input neurons are connected to hidden neurons based on the activations in the layer of input neurons, which allows for recurrent connections to be formed from hidden neurons back onto the input neurons. An activation pattern of the input neurons is then identified upon stabilization of the input neurons in the layer of input neurons. The activation pattern is a restored pattern, which allows the system to identify the object by comparing the restored pattern against stored patterns in a relational database. Based upon the object identification, a device, such as a robotic arm, etc., can then be controlled.
SPARSE ASSOCIATIVE MEMORY FOR IDENTIFICATION OF OBJECTS