Thesis Details
Fault tolerant Field Programmable Neural Networks
Ph.D. Thesis
Student: Krčma Martin
Academic Year: 2022/2023
Supervisor: Drábek Vladimír, doc. Ing., CSc.
Czech title
Field Programmable Neural Networks odolná proti poruchám
Language
English
Abstract
This thesis focuses on the Field Programmable Neural Networks concept intended to make implementation of neural networks in FPGAs less resource demanding. The thesis introduces and discusses several types of Field Programmable Neural Networks which provide different trad-offs between the resource consumption and the accuracy of the implemented neural network approximation. This thesis also introduces and discusses methods of hardening the Field Programmable Neural Networks against faults with and without redundancy.
Keywords
Field Programmable Neural Networks, fault tolerance, neural networks, FPGAs
Department
Degree Programme
Computer Science and Engineering, Field of Study
Computer Science and Engineering
Files
Status
defended
Date
20 March 2023
Citation
KRČMA, Martin. Fault tolerant Field Programmable Neural Networks. Brno, 2022. Ph.D. Thesis. Brno University of Technology, Faculty of Information Technology. 2023-03-20. Supervised by Drábek Vladimír. Available from: https://www.fit.vut.cz/study/phd-thesis/1503/
BibTeX
@phdthesis{FITPT1503, author = "Martin Kr\v{c}ma", type = "Ph.D. thesis", title = "Fault tolerant Field Programmable Neural Networks", school = "Brno University of Technology, Faculty of Information Technology", year = 2023, location = "Brno, CZ", language = "english", url = "https://www.fit.vut.cz/study/phd-thesis/1503/" }