Indexing of Image Databases Using Untrained 4D Holographic Memory Model
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
| Hi-index | 0.00 |
This paper presents the performance analysis of multidimensional holographic associative memory (MHAC). MHAC has the unique ability to retrieve pattern-associations with changeable attention. In attention actuated retrieval the user can dynamically select any subset of the elements in the example query pattern and expect the memory to confine its associative match only within the specified field of attention. MHAC, with the unique ability of localizable attention, can retrieve information correctly even with cues as small as 10% of the query frame. This paper investigates the performance of MHAC in attention actuated retrieval both analytically and experimentally. Besides confirmation, the experiments also identify an operational range space for this memory within which various attention based applications can be built with a performance guarantee