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A survey of software and hardware use in artificial neural networks

  • New applications of Artificial Neural Networks in Modeling & Control
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Abstract

Artificial neural networks (ANNs) have been widely used over the last three decades. During this period, many hardware and software solutions have been developed and today a new user entering the field can make a fast trial to this artificial intelligence solution with commercial software and hardware, instead of developing a solution from scratch thus saving a lot of time. This work aims at helping new and experienced users even further by sharing the ANNs experience in software and hardware collected. This was achieved through a survey questionnaire about present and past used solutions of software and hardware, as well as future prospects for the development of application areas. To further enlighten the reader, a logistic regression (LR) statistical analysis is performed on the obtained results to extract additional details about the answers obtained from the ANN community. The LR statistical analysis verifies whether the researchers with more than 25 years of experience in ANNs use self-written code when compared to those with less years of experience in the area. The LR statistical analysis also verifies whether researchers with less than 25 years of experience in ANNs use some platform to develop their hardware when compared to those who have more years of experience.

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Acknowledgments

The authors would like to acknowledge the Portuguese Foundation for Science and Technology for their support for this work through project PEst-OE/EEI/LA0009/2011.

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Authors and Affiliations

  1. Madeira Interactive Technologies Institute and Competence Center of Exact Science and Engineering, University of Madeira, 9000-390, Funchal, Portugal

    Darío Baptista, Sandy Abreu, Filipe Freitas, Rita Vasconcelos & Fernando Morgado-Dias

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  1. Darío Baptista
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  3. Filipe Freitas
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Correspondence to Darío Baptista.

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Baptista, D., Abreu, S., Freitas, F. et al. A survey of software and hardware use in artificial neural networks. Neural Comput & Applic 23, 591–599 (2013). https://doi.org/10.1007/s00521-013-1406-y

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  • DOI: https://doi.org/10.1007/s00521-013-1406-y

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