期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：1982
卷号：79
期号：6
页码：2091-2095
DOI：10.1073/pnas.79.6.2091
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Two parallel sets of selective networks composed of intercommunicating neuron-like elements have been connected to produce a new kind of automaton capable of limited recognition of two-dimensional patterns. Salient features of this automaton are (i) preestablished unchanging connectivity, (ii) preassigned connection strengths that are selectively altered according to experience, (iii) local feature detection in one network with simultaneous global feature correlation in the other, and (iv) reentrant interactions between the two networks to generate a new function, associative memory. No forced learning, explicit semantic rules, or a priori instructions are used.
