Abstract
The time characteristics of a linear network in the brain are obtained by the method of the “time partition function,” which is analogous to a grand partition function or a distribution function in statistical mechanics. The analogy between the average density in a many-particle system and the reciprocal of the frequency in a network is shown. By this method, the frequency distribution functions are obtained with respect to a network composed of two layers, the network used in information retrieval and the network generating a brain wave.
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References
R. Suzuki, I. Katsuno, and K. Matano,Kybernetik 1:39 (1971).
B. D. Burns,The Mammalian Cerebral Cortex, Edward Arnold, London (1958).
N. Tsukahara and T. Bando,Brain Research 10:295 (1970).
B. G. Farley,Self-Organizing Systems 1962, Ed. by M. C. Yovitset al, Spartan Books, Washington, D. C. (1962), p. 535.
E. R. Hilgard and D. G. Marquis,Conditioning and Learning, Appleton (1940).
D. O. Hebb,The Organization of Behavior, Wiley, New York (1949).
E. R. Caianiello and A. De Luca,Kybernetik 3:1 (1966).
Terrell L. Hill,An Introduction to Statistical Thermodynamics, Addison-Wesley (1960), §§1, 7.
N. Saitô and M. Oonuki,J. Phys. Soc. Japan 29:69 (1970).
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Oonuki, M. Time partition function analysis of a neural network. J Stat Phys 6, 119–131 (1972). https://doi.org/10.1007/BF01023682
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DOI: https://doi.org/10.1007/BF01023682