Abstract
AbstractIn this paper we present a biorealistic model for the first part of the early vision processing by incorporating memristive nanodevices. The architecture of the proposed network is based on the organisation and functioning of the outer plexiform layer (OPL) in the vertebrate retina. We demonstrate that memristive devices are indeed a valuable building block for neuromorphic architectures, as their highly non-linear and adaptive response could be exploited for establishing ultra-dense networks with similar dynamics to their biological counterparts. We particularly show that hexagonal memristive grids can be employed for faithfully emulating the smoothing-effect occurring at the OPL for enhancing the dynamic range of the system. In addition, we employ a memristor-based thresholding scheme for detecting the edges of grayscale images, while the proposed system is also evaluated for its adaptation and fault tolerance capacity against different light or noise conditions as well as distinct device yields.
Highlights
In this paper we present a biorealistic model for the first part of the early vision processing by incorporating memristive nanodevices
These connections take place on the outer plexiform layer (OPL) in the vertebrate retina; form a highly dynamic system that enables the smoothing of optical inputs and catalyzes the enhancement of the retina's dynamic range, while the different parallel channels emerge after this point
We focus on the outer plexiform layer and eminently to the synaptic connections and corresponding signal propagation through these
Summary
In this paper we present a biorealistic model for the first part of the early vision processing by incorporating memristive nanodevices. In this paper we focus on the connection of the sensory and consecutive system of the retina, which is the first and common step in the visual information flow These connections take place on the outer plexiform layer (OPL) in the vertebrate retina; form a highly dynamic system that enables the smoothing of optical inputs and catalyzes the enhancement of the retina's dynamic range, while the different parallel channels emerge after this point. Our approach alleviates these issues by employing the latest biological knowledge [5], and an emerging nanoscale device that is used as a more adequate synapse emulator [23], the memristor This device exhibits a highly non-linear dynamic behaviour, which along its infinitesimal dimensions serves as an excellent building block for facilitating practical realisations of the highly complex synaptic networks constituting the OPL. The axons of the latter cells propagate the pre-processed visual information towards the brain, essentially forming the optic nerve, with ON cells depolarizing and OFF cells hyperpolarizing in accordance to the corresponding impulses
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