SO(2)-networks as neural oscillators

Authors:
Frank Pasemann;Manfred Hild;Keyan Zahedi
Affiliations:
Fraunhofer Institute for Autonomous Intelligent Systems, Schloss Birlinghoven, Sankt Augustin, Germany;Fraunhofer Institute for Autonomous Intelligent Systems, Schloss Birlinghoven, Sankt Augustin, Germany;Fraunhofer Institute for Autonomous Intelligent Systems, Schloss Birlinghoven, Sankt Augustin, Germany
Venue:
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Year:
2003

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Abstract

In this paper we present a functional lnoclel of spiking neuron intended for harclware implementation. The model allows the design of speed-and/or area-optimized architectures. Some features of biological spiking neurons are abstracted, while preserving the functionality of the network, in order to define an architecture easily implementable in hardware, mainly in field programmable gate arrays (FPGA). The mnoclel pennits to optimize the architecture following area or speed criteria according to the application. In the same way, several parameters and features are optional, so as to allow more biologically plausible models by increasing the complexity and hardware requirements of the model. We present the results of three example applications performal to verify the computing capabilities of a simple instance of our model.