CHEMICAL IMPLEMENTATION AND THERMODYNAMICS OF COLLECTIVE NEURAL NETWORKS

被引：50

作者：

HJELMFELT, A ^{[1
]}

ROSS, J ^{[1
]}

机构：

[1] STANFORD UNIV,DEPT CHEM,STANFORD,CA 94305

来源：

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | 1992年 / 89卷 / 01期

关键词：

D O I：

10.1073/pnas.89.1.388

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The chemical implementation of a neuron and connections among neurons described in prior work is used to construct collective neural networks. With stated approximations, these chemical networks are reduced to networks of the Hopfield type. Chemical networks approaching a stationary or equilibrium state provide a Liapunov function with the same extremal properties as Hopfield's energy function. Numerical comparisons of chemical and Hopfield networks with small numbers (2-16) of neurons show agreement on the results of given computations.

引用

页码：388 / 391

页数：4

共 20 条

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Bender Carl, 1999, ADV MATH METHODS SCI, V1

[2]

Haken H., 1977, SYNERGETICS

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