Learning Patterns and Pattern Sequences by Self-Organizing Nets of Threshold Elements
- 1 November 1972
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Computers
- Vol. C-21 (11) , 1197-1206
- https://doi.org/10.1109/t-c.1972.223477
Abstract
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.Keywords
This publication has 11 references indexed in Scilit:
- Associatron-A Model of Associative MemoryIEEE Transactions on Systems, Man, and Cybernetics, 1972
- Correlation Matrix MemoriesIEEE Transactions on Computers, 1972
- Characteristics of randomly connected threshold-element networks and network systemsProceedings of the IEEE, 1971
- On Autonomous Logic Nets of Threshold ElementsIEEE Transactions on Computers, 1968
- Reverberations and control of neural networksBiological Cybernetics, 1967
- A Theory of Adaptive Pattern ClassifiersIEEE Transactions on Electronic Computers, 1967
- Nets of threshold elementsInformation and Control, 1965
- A Geometric Convergence Theorem for the PerceptronJournal of the Society for Industrial and Applied Mathematics, 1963
- Analysis of a Four-Layer Series-Coupled Perceptron. IIReviews of Modern Physics, 1962
- Outline of a theory of thought-processes and thinking machinesJournal of Theoretical Biology, 1961