Research on Virtual-Switch Characteristics of Noise-Enhanced Stochastic Resonance Using Leaky Integrate-and-Fire Model

Guo Hua Hui

doi:10.4028/www.scientific.net/KEM.439-440.1324

Paper Titles

The Application of Bayesian Neural Network in Rainfall Forecasting
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Research on NMF Based Hierarchical Clustering Methods
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The Design of an Enterprise Information Resource Management Platform Based on IRP
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A New Privacy Preserving Approach Used in Cloud Computing
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Research on Virtual-Switch Characteristics of Noise-Enhanced Stochastic Resonance Using Leaky Integrate-and-Fire Model
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Study on the Integrated Modeling of the Entire Rider-Vehicle-Road System
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Deciding the ALCNI_R₊-Satisfiability with a Fully Tiered Clause
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Test Investigation of Velocity Distribution Considering Snow Particles Participating
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Outdoor Test of Wind-Drifted Snow Distribution around a Cube
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HomeKey Engineering MaterialsKey Engineering Materials Vols. 439-440Research on Virtual-Switch Characteristics of...

Research on Virtual-Switch Characteristics of Noise-Enhanced Stochastic Resonance Using Leaky Integrate-and-Fire Model

Abstract:

Virtual-switch characteristics of noise-induced stochastic resonance using leaky integrate-and-fire (LIF) model was focused in this article. For LIF neuron model, Gaussian white noise was added to the simulating system. The condition of spike-starting was studied through the system. With the increase of noise intensity, the stimulated spikes became more and more intensive. With proper white noise intensity, the amount of excitatory spikes was enough to generate spike trains. We expected to design a virtual-switch utilizing this mechanism for neural data processing field.