Search for Articles:

MECS Press Menu

Mohammed J. Alhaddad

Work place: Faculty of Computing and Information Technology King Abdulaziz University KAU, Jeddah, Saudi Arabia

E-mail: Malhaddad@kau.edu.sa

Website:

Research Interests: Data Structures and Algorithms, Data Mining, Network Security, Artificial Intelligence

Biography

Dr. Mohammed J. Alhaddad received his Master from Essex University in 2001, and he obtained PhD from the school of Computer Science and Electronic Engineering, University of Essex in 2006, UK. He became Chairman of Information Technology Department at King Abdul-Aziz University. His research interests are: network Security, Artificial Intelligence, Robots, Brain Computer Interface BCI, and Radio Frequency Identification RFID, Data Mining, Semantic
Optimization, co-operative query databases and Deductive databases.

Author Articles
EEG based Autism Diagnosis Using Regularized Fisher Linear Discriminant Analysis

By Mahmoud I. Kamel Mohammed J. Alhaddad Hussein M. Malibary Khalid Thabit Foud Dahlwi Ebtehal A. Alsaggaf Anas A. Hadi

DOI: https://doi.org/10.5815/ijigsp.2012.03.06, Pub. Date: 8 Apr. 2012

Diagnosis of autism is one of the difficult problems facing researchers. To reveal the discriminative pattern between autistic and normal children via electroencephalogram (EEG) analysis is a big challenge. The feature extraction is averaged Fast Fourier Transform (FFT) with the Regulated Fisher Linear Discriminant (RFLD) classifier. 
Gaussinaty condition for the optimality of Regulated Fisher Linear Discriminant (RFLD) has been achieved by a well-conditioned appropriate preprocessing of the data, as well as optimal shrinkage technique for the Lambda parameter. Winsorised Filtered Data gave the best result.

[...] Read more.
Other Articles

Subscribe to receive issue release notifications and newsletters from MECS Press journals