Bio-Inspired Computation: Clock-Free, Grid-Free, Scale-Free and Symbol Free

Abstract

The project developed a new fundamental component for bio-inspired computing, based on a new way of modelling spiking neurons, and applying them to a new type of long-range temporal prediction task. The new model neuron has been applied to event-based data from a new type of motion sensitive camera - the neuromorphic Dynamic Vision Sensor (DVS). The model neuron incorporates temporal delays on both dendrites (inputs to neurons) and axons (outputs from neurons). Delays on axons have not previously been modeled in sensory-motor processing tasks, and their addition significantly simplifies asynchronous network development with spiking neurons, in particular reducing the computational complexity of algorithms for sparse data over dense sensory arrays. Effectively, the new model neuron treats each spike as a connection between temporal patterns extended in time in both its past and future.

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Document Details

Document Type
Technical Report
Publication Date
Jun 11, 2015
Accession Number
ADA626811

Entities

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  • Janet Wiles

Organizations

  • University of Queensland

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  • Abstracts
  • Air Force
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  • Computational Complexity
  • Computational Neuroscience
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Fields of Study

  • Computer science

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  • Computer Programming and Software Development.
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