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Meteorological Prediction Implemented on Field-Programmable Gate Array

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Abstract

In this work, a temperature predictor has been designed. The prediction is made by a multilayer perceptron neural network. Initially, the floating-point algorithm was evaluated. Afterward, the fixed-point algorithm was designed on a field-programmable gate array. The architecture was fully parallelized, and a maximum delay of 74 ns was obtained. The design tool used is a Xilinx system generator.

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Acknowledgments

This work has been supported by the Spanish Government, in particular by “Agencia Española de Cooperación Internacional para el Desarrollo” under the research projects with references D/027406/09 for 2010, D/033858/10 for 2011 and A1/039531/11 for 2012.

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Authors and Affiliations

  1. Department of Computer Science, Sede del Atlántico, University of Costa Rica, Turrialba, Cartago, Costa Rica

    José L. Vásquez

  2. Signals and Communications Department, Institute for Technological Development and Innovation in Communications, University of Las Palmas de Gran Canaria, Campus University of Tafira, Las Palmas de Gran Canaria, 35017, Las Palmas, Spain

    Santiago T. Pérez, Carlos M. Travieso & Jesús B. Alonso

Authors
  1. José L. Vásquez
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  2. Santiago T. Pérez
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  3. Carlos M. Travieso
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  4. Jesús B. Alonso
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Correspondence to José L. Vásquez.

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Vásquez, J.L., Pérez, S.T., Travieso, C.M. et al. Meteorological Prediction Implemented on Field-Programmable Gate Array. Cogn Comput 5, 551–557 (2013). https://doi.org/10.1007/s12559-012-9158-z

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  • DOI: https://doi.org/10.1007/s12559-012-9158-z

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