CAM-based ASOCS implementation

We describe an implementation of adaptive self-organizing concurrent system (ASOCS) using content addressable memory (CAM). ASOCS is an artificial neural network with supervised online 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.<
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