Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: Annual Conference of the IEEE-Industrial-Electronics-Society (IECON); Beijing, PEOPLES R CHINA; Beijing, PEOPLES R CHINA
Год издания: 2017
Аннотация: The main contribution of this paper is a study of the applicability of hyperdimensional computing and learning with an associative memory for modeling the dynamics of complex automation systems. Specifically, the problem of learning an evidence-based mode
Журнал: IECON 2017 - 43RD ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
Номера страниц: 3276-3281
ISSN журнала: 1553572X
Место издания: NEW YORK
Издатель: IEEE