Accurate detection of autism using Douglas-Peucker algorithm, sparse coding based feature mapping and convolutional neural network techniques with EEG signals
- 8 February 2022
- journal article
- research article
- Published by Elsevier in Computers in Biology and Medicine
- Vol. 143, 105311
Abstract
No abstract availableKeywords
Funding Information
- Deanship of Scientific Research, King Saud University
- King Abdulaziz University (498-135-14422)
This publication has 29 references indexed in Scilit:
- A Survey of Sparse Representation: Algorithms and ApplicationsIEEE Access, 2015
- GA-SELM: Greedy algorithms for sparse extreme learning machineMeasurement, 2014
- Robust features for the automatic identification of autism spectrum disorder in childrenJournal of Neurodevelopmental Disorders, 2014
- Automated diagnosis of autism: in search of a mathematical markerReviews in the Neurosciences, 2014
- Autism: cause factors, early diagnosis and therapiesReviews in the Neurosciences, 2014
- Global Prevalence of Autism and Other Pervasive Developmental DisordersAutism Research, 2012
- EEG complexity as a biomarker for autism spectrum disorder riskBMC Medicine, 2011
- Fractality and a Wavelet-Chaos-Neural Network Methodology for EEG-Based Diagnosis of Autistic Spectrum DisorderJournal Of Clinical Neurophysiology, 2010
- Mixed-Band Wavelet-Chaos-Neural Network Methodology for Epilepsy and Epileptic Seizure DetectionIEEE Transactions on Biomedical Engineering, 2007
- Compressed sensingIEEE Transactions on Information Theory, 2006