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FPGA-implementation of an adaptive neural network for RF power amplifier modeling

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2 Author(s)
Bahoura, M. ; Dept. of Eng., Univ. du Quebec a Rimouski, Rimouski, QC, Canada ; Chan-Wang Park

In this paper, we propose an architecture for FPGA-implementation of neural adaptive neural network RF power behavioral modeling. The real-valued time-delay neural network (RVTDNN) and the backpropagation (BP) learning algorithm were implemented on FPGA using Xilinx System Generator for DSP and the Virtex-6 FPGA ML605 Evaluation Kit. Performances obtained with 16-QAM modulated test signal and material resource requirement are presented for a network of six hidden layer neurons.

Published in:

New Circuits and Systems Conference (NEWCAS), 2011 IEEE 9th International

Date of Conference:

26-29 June 2011

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