{"pk":33111,"title":"Two Layer Digital RAAM","subtitle":null,"abstract":"We present modifications to Recursive Auto-Associative Memory which increase its robustness and storage capacity. This is done by introducing an extra layer to the compressor and reconstructor networks, employing integer rather than realvalued representations, pre-conditioning the weights and presetting the representations to be compatible with them, and using a quick-prop modification. Initial studies have shown this method to be reliable for data sets with up to three hundred subtrees.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"17","is_remote":true,"remote_url":"https://escholarship.org/uc/item/85d4p3mk","frozenauthors":[{"first_name":"Alan","middle_name":"D.","last_name":"Blair","name_suffix":"","institution":"Brandeis University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1995-01-01T21:00:00+03:00","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/33111/galley/24172/download/"}]}