A Neural Network Implementation On FPGA For Ecological Monitoring
Journal Title: Acta Technica Napocensis- Electronica-Telecomunicatii (Electronics and Telecommunications) - Year 2013, Vol 54, Issue 3
Abstract
In this paper, we present an implementation of an artificial neural network (ANN) for predicting blooms (coloured waters) of a species of toxic phytoplankton called Dinophysis acumunata that prevalent in coastal of Havre (France). A Multi-layer Perceptron (MLP) neural network is designed to predict the rate of algal cells concentration in a short time series. The processed data are extracted from analysis of average numerical values of physical and chemical parameters. The implementation of the designed neural network on FPGA (FPGA: Field Programmable Gate Array), a programmable circuit, help us to set up an automatic monitoring lagoon system.
Authors and Affiliations
Diaf YOUSSOUF, Kaddeche MOHAMED
Keywords
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