On Representations

--First, it was pointed out in this paper that there exists a hierarchical organization of entity to be represented by the neural networks. This hierarchical organization leads to four levels of correspondences between the entity, patterns, elements, items and the units. Then we classified representations further into more detailed categories from two viewpoints. From the correspondence viewpoint, representations can be classified into five categories: (1) local representation, (2) one-to-one DR, (3) one-to-many DR, (4) many-to-one DR, and (5) many-tomany DR. The second viewpoint of classifying representations is according to the locations where the representations exist. From the location viewpoint, representations fall into two classes: internal representation and external representation. Finally, it was pointed out that the origins of the confusion on representations may come from: (1) non-distinction of the hierarchical organization of entity, (2) non-distinction of the four levels of correspondences between the entity, patterns, elements, items and the units, (3) use of the too general or too broad term distributed representation, (4) non-distinction of the two levels of graceful degradation, and (5) non-distinction of similarities between different representations.