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
Status
delivered
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