The York Research Database
- » Research
- » York Research Database
- » Publications
- » Incorporating scale invariance into the cellular associative neural ne...
Incorporating scale invariance into the cellular associative neural network
Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review
Full text download(s)
incorporating-scale-invariance-into-the-cellular-associative-neural-network
200 KB, PDF document
Published copy (DOI)
Author(s)
Department/unit(s)
Publication details
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Date | Published - 1 Jan 2014 |
| Pages | 435-442 |
| Number of pages | 8 |
| Publisher | Springer-Verlag |
| Volume | 8681 LNCS |
| Original language | English |
| ISBN (Print) | 9783319111780 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 8681 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Abstract
This paper describes an improvement to the Cellular Associative Neural Network, an architecture based on the distributed model of a cellular automaton, allowing it to perform scale invariant pattern matching. The use of tensor products and superposition of patterns allows the system to recall patterns at multiple resolutions simultaneously. Our experimental results show that the architecture is capable of scale invariant pattern matching, but that further investigation is needed to reduce the distortion introduced by image scaling.
- associative memory, cellular automata, correlation matrix memory, distributed computation, pattern recognition, scale invariance
Research areas
Discover related content
Find related publications, people, projects, datasets and more using interactive charts.