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Deanship of Graduate Studies
Document Details
Document Type
:
Thesis
Document Title
:
FEATURE SELECTION & EXTRACTION ALGORITHMS FOR BRAIN COMPUTER INTERFACE
خوارزميات اختيار واستخلاص الخصائص المميزة لواجهة الدماغ الحاسوبية
Subject
:
Faculty of Computing and Information Technology-Computing Sciences
Document Language
:
Arabic
Abstract
:
A brain-computer interface (BCI) is a direct communication pathway between a human brain and an external device. In other words, a BCI allows users to act on their environment by using only brain activity, without using peripheral nerves and muscles. In BCI there are many paradigms; one of them is P300 which occurs in response to a significant but low-probability event. BCI data is considered to be high in their dimensionalities which reduce the system performance. Feature selection is a dimensionality reduction technique. Feature selection techniques study how to select a subset of features that enhance the performance of the system. The reason behind using feature selection techniques include reducing dimensionality, removing irrelevant and redundant features, reducing the amount of data needed for learning, and improving algorithms’ predictive accuracy. In this thesis, three types of feature selection techniques are compared and applied. These types are filter, wrapper, and hybrid. Fisher score, Determination Coefficient (r2), Regularized Fisher Linear Discriminant (RFLD), and Bayesian Linear Discriminant Analysis (BLDA) were used as evaluation functions. Differential Evolution (DE) optimization technique was used as searching technique. Two datasets were used to evaluate the results. Filter types were the preferred to be selected as feature selection method for P300 based BCI, in particular r2. This is due to the good reduction in dimension 64.8% and low computational cost 6.75ms. The time required for training and testing the classifier was improved by 83.62%.
Supervisor
:
Dr. Mahmoud Ibrahim Kamel Ali
Thesis Type
:
Master Thesis
Publishing Year
:
1434 AH
2013 AD
Added Date
:
Saturday, June 1, 2013
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
أنس عبد القادر هادي
Hadi, Anas Abdulqader
Researcher
Master
Files
File Name
Type
Description
35586.pdf
pdf
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