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Learning Patterns and Pattern Sequences by Self-Organizing Nets of Threshold Elements
November 1972 (vol. 21 no. 11)
pp. 1197-1206
S.-I. Amari, Department of Mathematical Engineering and Instrumentation Physics, University of Tokyo
Various information-processing capabilities of self-organizing nets of threshold elements are studied. A self-organizing net, learning from patterns or pattern sequences given from outside as stimuli, "remembers" some of them as stable equilibrium states or state-transition sequences of the net. A condition where many patterns and pattern sequences are remembered in a net at the same time is shown. The stability degree of their remembrance and recalling under noise disturbances is investigated theoretically. For this purpose, the stability of state transition in an autonomous logical net of threshold elements is studied by the use of characteristics of threshold elements.
Index Terms:
Associative memory, brain model, concept formation, logic nets of threshold elements, self-organization, sequential recalling, stability of state transition.
Citation:
S.-I. Amari, "Learning Patterns and Pattern Sequences by Self-Organizing Nets of Threshold Elements," IEEE Transactions on Computers, vol. 21, no. 11, pp. 1197-1206, Nov. 1972, doi:10.1109/T-C.1972.223477
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