Sigmoid function approximation for ANN implementation in FPGA devices

dc.contributor.authorKhodja, Djalal Eddine
dc.contributor.authorKheldoun, Aissa
dc.contributor.authorRefoufi, L.
dc.date.accessioned2015-06-17T13:11:05Z
dc.date.available2015-06-17T13:11:05Z
dc.date.issued2010
dc.description.abstractThe objective of this work is the implementation of Artificial Neural Network on a FPGA board. This implementation aim is to contribute in the hardware integration solutions in the areas such as monitoring, diagnosis, maintenance and control of power system as well as industrial processes. Since the Simulink library provided by Xilinx, has all the blocks that are necessary for the design of Artificial Neural Networks except a few functions such as sigmoid function. In this work, an approximation of the sigmoid function in polynomial form has been proposed. Then, the sigmoid function approximation has been implemented on FPGA using the Xilinx library. Tests results are satisfactoryen_US
dc.identifier.isbn978-960474262-2
dc.identifier.urihttps://dspace.univ-boumerdes.dz123456789/1992
dc.language.isoenen_US
dc.relation.ispartofseriesInternational conference on Circuits, Systems, Electronics, Control and Signal Processing - Proceedings (2010);pp. 112-116
dc.subjectANNen_US
dc.subjectFPGAen_US
dc.subjectPower systemen_US
dc.subjectSigmoid functionen_US
dc.subjectXilinxen_US
dc.titleSigmoid function approximation for ANN implementation in FPGA devicesen_US
dc.typeArticleen_US

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