Determining field of visual attention in associative memories

A new method of determining field of visual attention using associative memory is proposed. Paying attention to the typical features of the patterns plays a great role in recognition scheme of human beings. In conventional approaches, the field of visual attention is determined by the designers a priori and fixed while the systems are running. The proposed model is capable of determining the field of visual attention automatically. The proposed model is hierarchical network which consists of associative memory layer and feature layer. The connections between the layers represent the features of the input patterns and are generated automatically. These connections are modified through the Hebbian learning rule. In the proposed model, features are extracted through bottom-up procedure. The connections corresponding to the most excited unit in the feature layer are used as attention points in the top-down procedure. Through these procedures, the system is capable of associating appropriate patterns