Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/14711

Title: Implementation of decision trees for embedded systems
Authors: Badr, Bashar
Keywords: Decision tree learning
Real-time embedded systems
Incremental learning
Multi-dimensional frequency table
Hashed frequency table and field-programmable gate arrays
Issue Date: 2014
Publisher: © Bashar Badr
Abstract: This research work develops real-time incremental learning decision tree solutions suitable for real-time embedded systems by virtue of having both a defined memory requirement and an upper bound on the computation time per training vector. In addition, the work provides embedded systems with the capabilities of rapid processing and training of streamed data problems, and adopts electronic hardware solutions to improve the performance of the developed algorithm. Two novel decision tree approaches, namely the Multi-Dimensional Frequency Table (MDFT) and the Hashed Frequency Table Decision Tree (HFTDT) represent the core of this research work. Both methods successfully incorporate a frequency table technique to produce a complete decision tree. The MDFT and HFTDT learning methods were designed with the ability to generate application specific code for both training and classification purposes according to the requirements of the targeted application. The MDFT allows the memory architecture to be specified statically before learning takes place within a deterministic execution time. The HFTDT method is a development of the MDFT where a reduction in the memory requirements is achieved within a deterministic execution time. The HFTDT achieved low memory usage when compared to existing decision tree methods and hardware acceleration improved the performance by up to 10 times in terms of the execution time.
Description: A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.
Sponsor: Al-Ahliyya Amman University
Version: Not specified
URI: https://dspace.lboro.ac.uk/2134/14711
Appears in Collections:PhD Theses (Mechanical, Electrical and Manufacturing Engineering)

Files associated with this item:

File Description SizeFormat
Form-2014-Badr.pdf914.34 kBAdobe PDFView/Open
Thesis-2014-Badr.pdf3.66 MBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.