Field computation in natural and artificial intelligence

Information sciences

Volumn 119, Issue 1-2, 1999, Pages 73-89

  MacLennan, Bruce J ^a  

^a University of Tennessee Knoxville   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; COMPUTATIONAL METHODS; LEARNING ALGORITHMS; NEURAL NETWORKS;

ANALOG COMPUTATION; CONTINUUM COMPUTATION; CORTICAL MAP; FIELD COMPUTATION; HILBERT SPACE; MOLECULAR COMPUTER; MOLECULAR COMPUTING; QUANTUM COMPUTATION; QUANTUM COMPUTER; RADIAL BASIS FUNCTION;

ARTIFICIAL INTELLIGENCE;

EID: 0033207969     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0020-0255(99)00053-5     Document Type: Article

References (32)

1. Bizzi E., Mussa-Ivaldi F.A. Toward a neurobiology of coordinate transformation. Gazzaniga M.S. The Cognitive Neurosciences. 1995;495-506 MIT Press, Cambridge, MA.
2. Bohm D., Hiley B.J. The Undivided Universe: An Ontological Interpretation of Quantum Theory. 1993;Routledge, London.
3. J.-P. Changeux, Neuronal Man: The Biology of Mind (tr. by L. Garey), Oxford, 1985.
4. Daugman J.G. Spatial visual channels in the Fourier plane. Vision Res. 24:1984;891-910.
5. P.A.M. Dirac, The Principles of Quantum Mechanics, fourth ed., Oxford, 1958.
6. Droulez J., Berthoz A. The concept of dynamic memory in sensorimotor control. Humphrey D.R., Freund H.-J. Motor Control: Concepts and Issues. 1991;137-161 Wiley, New York.
7. J. Droulez, A. Berthoz, A neural network model of sensoritopic maps with predictive short-term memory properties, Proc. Natl. Acad. Sci. U.S.A. 88 (1991) 9653-9657.
8. Gabor D. Theory of communication. Journal of the Institution of Electrical Engineers. 93, Part III:1946;429-457.
9. Georgopoulos A.P. Motor cortex and cognitive processing. Gazzaniga M.S. The Cognitive Neurosciences. 1995;507-517 MIT Press, Cambridge, MA.
10. Hopfield J.J. Pattern recognition computation using action potential timing for stimulus representation. Nature. 376:1995;33-36.
11. S.C. Kak, in: K. Pribram, J. King (Eds.), The Three Languages of the Brain: Quantum Reorganizational and Associative, Lawrence Erlbaum, London, 1996, pp. 185-219.
12. Kak S.C. Quantum information in a distributed apparatus. Foundations of Physics. 28:1998;1005-1012.
13. Knudsen E.J., du Lac S., Esterly S.D. Computational maps in the brain. Ann. Rev. of Neuroscience. 10:1987;41-65.
14. D. Lowe, What have neural networks to offer statistical pattern processing? Proceedings of the SPIE Confernce on Adaptive Signal Processing, San Diego, 1991, pp. 460-471.
15. B.J. MacLennan, Technology-independent design of neurocomputers: The universal field computer, in: M. Caudill, C. Butler (Eds.), Proceedings of the IEEE First International Conference on Neural Networks, vol. 3, IEEE Press, New York, 1987, pp. 39-49.
16. B.J. MacLennan, Field computation: A theoretical framework for massively parallel analog computation, parts I-IV. Tech. Rep. CS-90-100, Computer Science Department, University of Tennessee, Knoxville, 1990. Accessible via URL http://www.cs.utk.edu/mclennan.
17. B.J. MacLennan, Gabor representations of spatiotemporal visual images, Tech. Rep. CS-91-144, Computer Science Department, University of Tennessee, Knoxville, 1991. Accessible via URL http://www.cs.utk.edu/mclennan.
18. MacLennan B.J. Information processing in the dendritic net. Pribram K. Rethinking Neural Networks: Quantum Fields and Biological Data. 1993;161-197 Lawrence Erlbaum, London.
19. MacLennan B.J. Field computation in the brain. Pribram K. Rethinking Neural Networks: Quantum Fields and Biological Data. 1993;199-232 Lawrence Erlbaum, London.
20. MacLennan B.J. Continuous computation and the emergence of the discrete. Pribram K. Origins: Brain & Self-Organization. 1994;121-151 Lawrence Erlbaum, London.
21. MacLennan B.J. Image and symbol: Continuous computation and the emergence of the discrete. Hanovar V., Uhr L. Artificial Intelligence and Neural Networks: Steps Toward Principled Integration, Volume I: Basic Paradigms; Learning Representational Issues; and Integrated Architectures. 1994;207-240 Academic Press, New York.
22. B.J. MacLennan, Continuous formal systems: A unifying model in language and cognition, Proceedings of the IEEE Workshop on Architectures for Semiotic Modeling and Situation Analysis in Large Complex Systems, 1995, pp. 161-172.
23. MacLennan B.J. Field computation in motor control. Morasso P., Sanguineti V. Self-Organization, Computational Maps and Motor Control. 1997;37-73 Elsevier, Amsterdam.
24. J.W. Mills, Kirkhoff machines, Technical Report, Computer Science Department, Indiana University, Bloomington, 1995.
25. Moody J.E., Darken C.J. Fast learning in networks of locally-tuned processing units. Neural Computation. 1:1989;281-294.
26. Peruš M. Neuro-quantum parallelism in brain-mind and computers. Informatica. 20:1996;173-183.
27. M. Peruš, A quantum information-processing "algorithm" based on neural nets, in: P. Wang, G. Georgiou, C. Janikow, Y. Yao (Eds.), JICS '98 Proceedings, vol. II, Assoc. for Intell. Mach., 1998, pp. 197-200.
28. Pribram K.H. Brain and Perception: Holonomy and Structure in Figural Processing. 1991;Lawrence Erlbaum, London.
29. Pribram K.H., Sharafat A., Beekman G.J. Frequency encoding in motor systems. Whiting H.T.A. Human Motor Actions - Bernstein Reassessed. 1984;121-156 Elsevier, Amsterdam.
30. Skinner S.R., Behrman E.C., Cruz-Cabrera A.A., Steck J.E. Neural network implementation using self-lensing media. Applied Optics. 34:1995;4129-4135.
31. D. Wettscherick, T. Dietterich, Improving the performance of radial basis function networks by learning center locations, in: J.E. Moody, S.J. Hanson, R.P. Lippmann (Eds.), Advances in Neural Information Processing Systems, vol. 4, Morgan Kaufmann, Los Altos, CA, 1992, 1133-1140.
32. D.H. Wolpert, B.J. MacLennan, A computationally universal field computer which is purely linear. See also Santa Fe Institute TR 93-09-056 and University of Tennessee, Knoxville, Computer Science Department, TR CS-93-206. Accessible via URL http://www.cs.utk.edu/ ̃ mclennan , submitted.