By the same authors

Autonomous navigational controller inspired by the hippocampus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

Department/unit(s)

Publication details

Title of host publication2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6
DatePublished - 2007
Pages813-818
Number of pages6
PublisherIEEE
Place of PublicationNEW YORK
Original languageEnglish
ISBN (Print)978-1-4244-1379-9

Abstract

This study uses models of pyramidal neurons in the hippocampus to design a hardware spiking neural network neuro-controller model for the purpose of navigation. The neural network model consists of individual neurons modeled using the two-dimensional bio-inspired Izhikevich algorithm. The network is connected according to the connectivity within the hippocampus region, as this region is one of the regions in the brain that is responsible for path navigation. The information processed by the model helps provide navigation and creates memories. The neural network model is intended to be implemented onto a Field Programmable Gate Array (FPGA) device. This eliminates the need of an operating system to run the network, thus achieving autonomy.

    Research areas

  • neural network architecture, neural network hardware, MODEL, OSCILLATIONS, ROBOTS

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