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An End User Platform for FPGA-based Design and Rapid Prototyping of FeedForward Artificial Neural Networks with on-chip Back Propagation learning
journal contribution
posted on 2023-08-30, 14:17 authored by Alin Tisan, Jeannette ChinThe hardware implementation of an Artificial Neural Network (ANN) using field-programmable gate arrays (FPGA) is a research field that has attracted much interest and attention. With the developments made, the programmer is now forced to face various challenges, such as the need to master various complex hardware-software development platforms, hardware description languages and advanced ANN knowledge. Moreover, such an implementation is very time consuming. To address these challenges, the paper presents a novel neural design methodology using a holistic modelling approach. Based on the end user programming concept, the presented solution empowers end users by means of abstracting the low-level hardware functionalities, streamlining the FPGA design process and supporting rapid ANN prototyping. A case study of an ANN as a pattern recognition module of an artificial olfaction system trained to identify four coffee brands is presented. The recognition rate versus training data features and data representation was analysed extensively.
History
Refereed
- Yes
Volume
12Issue number
3Page range
1124-1133Publication title
IEEE Transactions on Industrial InformaticsISSN
1941-0050External DOI
Publisher
IEEEFile version
- Accepted version
Language
- eng
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Legacy posted date
2016-06-15Legacy creation date
2016-08-24Legacy Faculty/School/Department
ARCHIVED Faculty of Science & Technology (until September 2018)Note
© © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksUsage metrics
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