Article detail · 2016
Hardware Implementation of Neural Network Training with Levenberg-Marquardt Algorithm
- Year
- 2016
- Type
- article
Abstract
OpenAlex · English
Hardware Implementation of Neural Network Training with Levenberg-Marquardt AlgorithmLevenberg-Marquardt (LM) algorithm is preferred due to providing fast convergence and stability in training of artificial neural networks (ANN). In this study, hardware implementation of ANN training with LM algorithm is presented on FPGA using floating point number representation..Hardware implementation has been realized on Virtex-5 xc5vlx110-3ff1153 FPGA using ISE Webpack 10.1 software. In this work, both ANN and its training using LM have been particularly implemented on FPGA according to the inherent parallel data processing of ANN. Obtained synthesis results have showed that training of ANN using LM algorithm can be successfully implemented on FPGA.
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Citations
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8 citations
OpenAlex cited_by_count (cache / database)
11 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
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