Context-dependent associations in linear distributed memories
- Eduardo Mizraji
- … show all 1 hide
Purchase on Springer.com
$39.95 / €34.95 / £29.95*
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.
In this article we present a method that allows conditioning of the response of a linear distributed memory to a variable context. This method requires a system of two neural networks. The first net constructs the Kronecker product between the vector input and the vector context, and the second net supports a linear associative memory. This system is easily adaptable for different goals. We analyse here its capacity for the conditional extraction of features from a complex perceptual input, its capacity to perform quasi-logical operations (for instance, of the kind of “exclusive-or”), and its capacity to structurate a memory for temporal sequences which access is conditioned by the context. Finally, we evaluate the potential importance of the capacity to establish arbitrary contexts, for the evolution of biological cognitive systems.
- Anderson, J.A. 1970. “Two Models for Memory Organization Using Interacting Traces”.Math. Biosci.,8, 137–160. CrossRef
- — 1972. “A Simple Neural Network Generating an Interactive Memory”.Math. Biosci. 14, 197–220. CrossRef
- — 1983. “Cognitive and Psychological Computation with Neural Models”.IEEE Trans. Systems. Man Cybernetics 13, 799–815.
- —, J. W. Silverstein, S. A. Ritz and R. S. Jones. 1977. “Distinctive Features, Categorical Perception, and Probability Learning: Some Applications of a Neural Model”.Psychol. Rev. 84, 413–451. CrossRef
- Ashby, W. R. 1958. “Requisite Variety and its Implications for the Control of Complex Systems”.Cybernetica 1, 83–99.
- Bellman, R. 1960.Introduction to Matrix Analysis. New York: McGraw-Hill.
- Changeux, J. P. and A. Danchin. 1976. “Selective Stabilization of Developing Synapses as a Mechanism for the Specification of Neuronal Networks”.Nature 264, 705–712. CrossRef
- Cooper, L. N. 1973. “A Possible Organization of Animal Memory and Learning.” In Proceedings of the Nobel Symposium on Collective Properties of Physical Systems, B. Lundquist and S. Lundquist (Eds) New York: Academic Press.
- Kohonen, T. 1977.Associative Memory: A System Theoretical Approach. New York: Springer.
- Monod, J. 1967. Leçon inaugurale, Collège de France.
- — and F. Jacob. 1963. “Allosteric Proteins and Cellular Control Systems.”J. Molec. Biol. 6, 306–329. CrossRef
- Nass, M. M. and L. N. Cooper. 1975. “A Theory for the Development of Feature Detecting Cells in Visual Cortex”.Biol. Cybernetics 19, 1–18. CrossRef
- Ribchester, R. R. 1986.Molecule, Nerve and Embryo. Glasgow: Blackie.
- Rumelhart, D. E., G. E. Hinton and J. L. McClelland. 1986. “A General Framework for Parallel Distributing Processing”. InParallel Distributing Processing, D. E. Rumelhart and J. L. McClelland (Eds). Massachusetts: MIT Press.
- —— and R. J. Williams. 1986. “Learning Representations by Back-Propagating Errors”.Nature 323, 533–536. CrossRef
- Stone, G. O. 1986. “An Analysis of the Delta Rule and the Learning of Statistical Associations”. InParallel Distributing Processing, D. E. Rumelhart and J. L. McClelland (Eds). Massachusetts: MIT Press.
- Context-dependent associations in linear distributed memories
Bulletin of Mathematical Biology
Volume 51, Issue 2 , pp 195-205
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- Eduardo Mizraji (1) (2)
- Author Affiliations
- 1. Sección Biofísica, Facultad de Humanidades y Ciencias, Montevideo, Uruguay
- 2. Departmento de Biofísica, Facultad de Medicina, Montevideo, Uruguay