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Application the Spiking Neuron Model with Structural Adaptation to Describe Neuromorphic Systems

Aleksandr Bakhshiev, Filipp Gundelakh

Year
2017
Citations
4

Abstract

The paper discusses the architectural elements of neuromorphic systems on the example of behaviour control of robots. The basis of the work is new spiking neuron model, which allows describing the known biological network relying on macroscopic parameters of neurons - the size, the relative length of dendrites, etc. The model also allows no parametric setting but change synaptic and dendritic structures. This implies the possibility of a structural adjustment neuromorphic system. The paper gives examples of simulation results of the proposed elements neuromorphic systems.

Keywords

Neuromorphic engineeringComputer scienceSpiking neural networkBiological neuron modelAdaptation (eye)Artificial intelligenceParametric statisticsArtificial neural networkRobotNeuroscience

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