Artificial Neural Systems: Principle and Practice

Basic Neurons

Author(s): Pierre Lorrentz

Pp: 15-27 (13)

DOI: 10.2174/9781681080901115010004

* (Excluding Mailing and Handling)


The aim and objectives of this chapter is to present other types of artificial neuromorphic neurons with capability of reset and recovery. For this reason, the first section starts with the integrate-and-fire neuron, which has the propensity for reset. The second section introduces probability theory owing to the fact that many processes in the brain and central nervous system obey probability laws. The third section introduces another artificial neuromorphic neuron which employs a Poisson process and is closer in behaviour to a biological neuron.

Keywords: Bayes theorem, Binomial, Bernoulli, Charging, Depolarization, Density function, Excitatory, Expected-value, Inhibitory, Mean, Moment, ODE, Pseudo-random-number-generator, Poisson, Steady-state, Synaptic strength, Spike, Threshold potential, Uniform distribution, Variance.

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