| Автор | Chun-Hsien, Chen |
| Автор | Honavar, Vasant |
| Дата выпуска | 1995 |
| dc.description | This paper presents an approach to design of a neural architecture for both associative (content-addressed) and address-based memories. Several interesting properties of the memory module are mathematically analyzed in detail. When used as an associative memory, the proposed neural memory module supports recall from partial input patterns, (sequential) multiple recalls and fault-tolerance. When used as an address-based memory, the memory module can provide working space for dynamic representations for symbol processing and shared message-passing among neural network modules within an integrated neural network system. It also provides for real-time update of memory contents by one-shot learning without interference with other stored patterns. |
| Формат | application.pdf |
| Издатель | Taylor & Francis Group |
| Копирайт | Copyright Taylor and Francis Group, LLC |
| Тема | Associative Memory Content-ADDRESSED Memory Fault-TOLERANCE Multiple Associative Recall Adjustable-PRECISION Memory Binary Mappings Information Retrieval Address-BASED Memory High-CAPACITY Memory Interference |
| Название | Associative Memory Content-ADDRESSED Memory Fault-TOLERANCE Multiple Associative Recall Adjustable-PRECISION Memory Binary Mappings Information Retrieval Address-BASED Memory High-CAPACITY Memory Interference |
| Тип | research-article |
| DOI | 10.1080/09540099509696194 |
| Electronic ISSN | 1360-0494 |
| Print ISSN | 0954-0091 |
| Журнал | Connection Science |
| Том | 7 |
| Первая страница | 281 |
| Последняя страница | 300 |
| Выпуск | 3-4 |
