Modeling of neural decoder based on binary spiking neurons in DEVS

  • Authors:
  • Yuri Boiko;Gabriel Wainer

  • Affiliations:
  • Carleton University, Ottawa, ON, Canada;Carleton University, Ottawa, ON, Canada

  • Venue:
  • SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
  • Year:
  • 2009

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Abstract

Presented here is the simulation of specific application of reported earlier Binary Spiking Neurons for implementation of the Binary Neural Spiking Decoder, thus attaining next level in hierarchy of the Brain Machine devices based on the binary spiking neurons. This further extends the simulation of selected elements of Brain Machine in DEVS environment employing CD++ toolkit. Targeted applications include development of high throughput communication channels, employing spike encoding -- decoding technique at high frequencies. Neural decoder based on binary spiking neurons is chosen for modeling in DEVS formal definitions as top model, which in turn is using previously reported atomic and coupled model associated with binary spiking neurons. In this application the signal of the encoded in ternary alphabet test messages of spike sequences is employed to verify functionality of the resulting spiking neural decoder. Spike sequences are split between two channels -- one for initiating spikes and another one for terminating ones. Binary spiking neurons, which by definition have a rectangular response function, are considered in the presented model. Firing condition for the binary spiking neuron is reached when two rectangular responses, one for the initiating spike and another one for terminating spike, overlap in time domain, as a result producing "1" at the neuron's output (firing signal) or alternatively "0" (non-firing output signal).