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On the effects of boundary conditions on CNN dynamics: stability and instability, bifurcation processes and chaotic phenomena
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Biomimetic model of the outer plexiform layer by incorporating memristive devices
No full textIn this paper we present a biorealistic model for the first part of the early vision of processing by incorporating memristive nanodevices. The architecture of the proposed network is based on the organization 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 nonlinear and adaptive response could be exploited for establishing ultradense networks with dynamics similar to that of their biological counterparts. We particularly show that hexagonal memristive grids can be employed for faithfully emulating the smoothing effect occurring in the OPL to enhance 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 its distinct device yields
Synchronization in cellular spin torque oscillator arrays
No full textSpin torque nanodevices could provide a platform for computation beyond Moore's law. The network of spin oscillators can have only local, cellular interconnections because of the underlying physics: the interaction between the oscillators happens through the magnetic field. In this paper we describe the dynamics of weakly coupled spin-torque oscillator networks and how the dynamics of these cellular arrays can be used for problem solving. We will describe how the phase shift in a synchronized array can be calculated between the elements and we will also show a simple example how the dynamics of a cellular array can be used to solve simple tasks
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