Dynamic connections in neural networks

Jerome A. Feldman

doi:10.1007/bf00335349

journal article Dec 01, 1982

Dynamic connections in neural networks

Jerome A. Feldman

Biological Cybernetics Vol. 46 No. 1 pp. 27-39 · Springer Science and Business Media LLC

View at Publisher Save 10.1007/bf00335349

Topics

No keywords indexed for this article. Browse by subject →

References

32

[1]

Anderson, J.R., Bower, G.H.: Human associative memory. Washington, DC: V.H. Winston and Sons 1972

[2]

Ballard, D.H.: Parameter networks. TR 75, Computer Science Dept., U. Rochester, 1981; Proc. 7th IJCAI, Vancouver, B.C., August 1981

[3]

Barto, A.G., Sutton, R.S., Brouwer, P.S.: Associative search network: a reinforcement learning associative memory. Biol. Cybern.40, 201–211 (1981) 10.1007/bf00453370

[4]

Buser, P.A., Roguel-Buser, A. (eds): Cerebral correlates of conscious experience. Amsterdam: North-Holland 1978

[5]

Cotman, C.W. (ed): Neuronal plasticity. New York: Raven Press 1978

[6]

Dell, G.S., Reich, P.A.: Toward a unified model of slips of the tonguc. In: Errors in linguistic performance: slips of the tongue, car, pen, and hand. Fromkin, V.A. (ed) New York: Academic Press 1980

[7]

Dev, P.: Perception of depth surfaces in random-dot stereograms: a neural model. Intl. J. Man-Machine Stud.7, 511–528 (1975) 10.1016/s0020-7373(75)80030-7

[8]

Doty, R.W.: Neurons and memory: some clues. In: Brain mechanisms in memory and learning: from the single neuron to man, Brazier, M.A.B. Int. J. Brain Research Organization Monograph Series, Vol. 4. New York: Raven Press 1979

[9]

Fahlman, S.E.: The Hashnet interconnection scheme. Computer Science Dept. Carnegie-Mellon U., June 1980

[10]

Feldman, J.A.: Four frames suffice. TR 99, Computer Science Dept., U. Rochester 1982

[11]

Feldman, J.A.: A connectionist model of visual memory. In: Parallel models of associative memory. Hinton, G.E., Anderson, J.A. (eds.) Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers 1981a

[12]

Feldman, J.A.: Memory and change in connection networks. TR 96, Computer Science Dept., U. Rochester 1981b

[13]

Feldman, J.A., Ballard, D.H.: Connectionist models and their properties. Cogn. Sci. 1982 (to appear) 10.1207/s15516709cog0603_1

[14]

Feldman, J.A., Nigam, A.: A model and proof technique for message-based systems. SIAM J. Comput.9, 4 (1980) 10.1137/0209060

[15]

Grossberg, S.: Biological competition: decision rules, patterm formation, and oscillations. Proc. Natl. Acad. Sci. USA77, 4, 2238–2342 (1980) 10.1073/pnas.77.4.2338

[16]

Hanson, A.R., Riseman, E.M. (eds): Computer vision systems. New York: Academic Press 1978

[17]

Hinton, G.E., Anderson, J.A. (eds): Parallel models of associative memory. Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers 1981

[18]

Jusczyk, P.W., Klein, R.M. (eds): The nature of thought: essays in honour of D.O. Hebb. Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers 1980

[19]

Kandel, E.R.: The cellular basis of behavior. San Francisco, CA: Freeman 1976

[20]

Marr, D.C.: Vision. San Francisco, CA: Freeman 1980

[21]

Marr, D.C., Poggio, T.: Cooperative computation of stereo disparitly. Science194, 283–287 (1976) 10.1126/science.968482

[22]

McClelland, J.L., Rumelhart, D.E.: An interactive activation model of the effect of context in perception. Part 1. Psych. Rev. (to appear)

[23]

Minsky, M., Papert, S.: Perceptrons. Cambridge, MA: The MIT Press 1972

[24]

Pippenger, N.: On rearrangeable and non-blocking switching networks. J. Comput. Syst. Sci.17, 2, October (1978) 10.1016/0022-0000(78)90001-6

[25]

Posner, M.I.: Chronometric explorations of mind. Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers 1978

[26]

Richter, J., Ullman, S.: A model for the temporal organization ofX-andY-type receptive fields in the primate retina. Biol. Cybern.43, 127–145 (1982) 10.1007/bf00336975

[27]

Sabbah, D.: Design of a highly parallel visual recognition system. Proc. 7th IJCAI, Vancouver, B.C., August 1981

[28]

Sleeman, D., Langley, P., Mitchell, T.M.: Learning from solution paths: an approach to the credit assignment problem. The AI Magazine, Spring 48–52 (1982)

[29]

Stent, G.S.: A physiological mechanism for Hebb's postulate of learning. Proc. Natl. Acad. Sci. USA70, 4, 997–1001 (1973) 10.1073/pnas.70.4.997

[30]

Sutton, R.S., Barto, A.G.: Toward a modern theory of adaptive networks: expectation and prediction. Psychol. Rev.88, 2, 135–170 (1981) 10.1037/0033-295x.88.2.135

[31]

Torioka, T.: Pattern separability in a random neural net with inhibitory connections. Biol. Cybern.34, 53–62 (1979) 10.1007/bf00336858

[32]

Wickelgren, W.A.: Chunking and consolidation: a theoretical synthesis of semantic networks. configuring in conditioning,S-R versus cognitive learning, normal forgetting, the amnesic syndrome, and the hippocampal arousal system. Psychol. Rev.86, 44–60 (1979) 10.1037/0033-295x.86.1.44

Metrics

173

Citations

32

References

Details

Published: Dec 01, 1982
Vol/Issue: 46(1)
Pages: 27-39
License: View

Authors

J

Jerome A. Feldman

Cite This Article

Jerome A. Feldman (1982). Dynamic connections in neural networks. Biological Cybernetics, 46(1), 27-39. https://doi.org/10.1007/bf00335349

Dynamic connections in neural networks

You May Also Like