DocumentCode :
1346749
Title :
Logic operations based on single neuron rational model
Author :
Zhang, Chang Nian ; Zhao, Ming ; Wang, Meng
Author_Institution :
Dept. of Comput. Sci., Regina Univ., Sask., Canada
Volume :
11
Issue :
3
fYear :
2000
fDate :
5/1/2000 12:00:00 AM
Firstpage :
739
Lastpage :
747
Abstract :
This paper focuses on phase analysis to explore the single neuron local arithmetic and logic operations on their input conductances. Based on the analysis of the rational function model of local spatial summation with the equivalent circuits for steady-state membrane potentials, the prototypes spatial summation with the equivalent circuits for steady-state membrane potentials, the prototypes of logic operations are constructed. A mapping from a partition of input conductance space into functionally distinct phases is described and the multiple mode models for logic operations are established. The transitions from output voltage to input conductance in logic operations are also discussed for the connections between neurons in different layers. Our theoretical studies and software simulations indicate that the single neuron local rational logic is programmable and the selection of these functional phases can be effectively instructed by presynaptic activities. This programmability makes the single neuron more flexible in processing the input information
Keywords :
digital arithmetic; multilayer perceptrons; neural chips; rational functions; functional phases; functionally distinct phases; input conductance space partition; input conductances; local rational logic; local spatial summation; logic operations; phase analysis; presynaptic activities; programmability; programmable logic; prototype spatial summation; rational function model; single neuron local arithmetic operations; single neuron rational model; software simulations; steady-state membrane potentials; Artificial neural networks; Biological neural networks; Biological system modeling; Biology computing; Biomembranes; Computational modeling; Equivalent circuits; Logic; Neurons; Prototypes;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.846745
Filename :
846745
Link To Document :
بازگشت