1. A reference data recognition and learning method of reference data recognition and learning with respect to an associative memory, which compares input search data with several reference data to select and output the most similar reference data, comprising: giving a rank corresponding to a priority to each of the several reference data stored in the associative memory; comparing the search data with the several reference data when the search data is input to detect a similarity between the search data and each of the several reference data, and selecting reference data having the highest similarity; and determining whether or not the search data and the reference data selected by the comparing are identical to each other from their similarity, wherein the giving the rank includes controlling the rank such that a rank of the reference data selected by the comparing is improved by a predetermined number while a rank of other reference data equal to or lower than the improved rank is reduced when the search data and the reference data selected by the comparing are determined to be identical in the determining, and when the rank is controlled, a long-term memory hierarchy and a short-term memory hierarchy, each including an arbitrary number of ranks are formed, and when the search data and the reference data selected by the comparing are determined not to be identical in the determining, the search data are registered to an uppermost rank of the short-term memory hierarchy as new reference data, and when the search data are determined to be identical to the reference data in the short-term memory hierarchy, the registration of the search data is shifted to a predetermined rank of the long-term memory hierarchy and thereafter the rank of the reference data in the long-term memory hierarchy determined to be identical to the search data in the determining is increased by the predetermined number.