CAM-based ASOCS implementation
Document Type
Conference Proceeding
Date of Original Version
12-1-1994
Abstract
We describe an implementation of Adaptive Self-Organizing Concurrent System (ASOCS) using Content Addressable Memory (CAM). ASOCS is an artificial neural network with supervised on-line learning trained by incrementally introduced boolean propositional logic rules or instances. Words stored in CAM represent modified instances after they are processed by ASOCS to ensure consistency and minimality of the entire collection of instances. CAM permits fast training and execution. Main advantages of our implementation are simplicity, scalability to handle wider input and output vectors, ability to preset the network structure in advance based on software simulation.
Publication Title, e.g., Journal
IEEE International Conference on Neural Networks - Conference Proceedings
Volume
4
Citation/Publisher Attribution
Bartczak, Andrew, and James Daly. "CAM-based ASOCS implementation." IEEE International Conference on Neural Networks - Conference Proceedings 4, (1994): 2103-2107. https://digitalcommons.uri.edu/ele_facpubs/191