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- Hojjat Adeli, Ziqin Zhou, Nahid Dadmehr
- Journal of neuroscience methods
- 2003

About 1% of the people in the world suffer from epilepsy and 30% of epileptics are not helped by medication. Careful analyses of the electroencephalograph (EEG) records can provide valuable insight and improved understanding of the mechanisms causing epileptic disorders. Wavelet transform is particularly effective for representing various aspects of… (More)

- Hojjat Adeli, Samanwoy Ghosh-Dastidar, Nahid Dadmehr
- IEEE Trans. Biomed. Engineering
- 2007

A wavelet-chaos methodology is presented for analysis of EEGs and delta, theta, alpha, beta, and gamma subbands of EEGs for detection of seizure and epilepsy. The nonlinear dynamics of the original EEGs are quantified in the form of the correlation dimension (CD, representing system complexity) and the largest Lyapunov exponent (LLE, representing system… (More)

- Hojjat Adeli
- 2000

The first journal article on neural network application in civil/structural engineering was published in this journal in 1989. This article reviews neural network articles published in archival research journals since then. The emphasis of the review is on the two fields of structural engineering and construction engineering and management. Neural networks… (More)

- Samanwoy Ghosh-Dastidar, Hojjat Adeli, Nahid Dadmehr
- IEEE Trans. Biomed. Engineering
- 2008

A novel principal component analysis (PCA)-enhanced cosine radial basis function neural network classifier is presented. The two-stage classifier is integrated with the mixed-band wavelet-chaos methodology, developed earlier by the authors, for accurate and robust classification of electroencephalogram (EEGs) into healthy, ictal, and interictal EEGs. A… (More)

- Samanwoy Ghosh-Dastidar, Hojjat Adeli, Nahid Dadmehr
- IEEE Trans. Biomed. Engineering
- 2007

A novel wavelet-chaos-neural network methodology is presented for classification of electroencephalograms (EEGs) into healthy, ictal, and interictal EEGs. Wavelet analysis is used to decompose the EEG into delta, theta, alpha, beta, and gamma sub-bands. Three parameters are employed for EEG representation: standard deviation (quantifying the signal… (More)

- Samanwoy Ghosh-Dastidar, Hojjat Adeli
- Integrated Computer-Aided Engineering
- 2007

- Ashif Panakkat, Hojjat Adeli
- Int. J. Neural Syst.
- 2007

Neural networks are investigated for predicting the magnitude of the largest seismic event in the following month based on the analysis of eight mathematically computed parameters known as seismicity indicators. The indicators are selected based on the Gutenberg-Richter and characteristic earthquake magnitude distribution and also on the conclusions drawn… (More)

- Samanwoy Ghosh-Dastidar, Hojjat Adeli
- Neural Networks
- 2009

A new Multi-Spiking Neural Network (MuSpiNN) model is presented in which information from one neuron is transmitted to the next in the form of multiple spikes via multiple synapses. A new supervised learning algorithm, dubbed Multi-SpikeProp, is developed for training MuSpiNN. The model and learning algorithm employ the heuristic rules and optimum parameter… (More)

- Samanwoy Ghosh-Dastidar, Hojjat Adeli
- Int. J. Neural Syst.
- 2009

Most current Artificial Neural Network (ANN) models are based on highly simplified brain dynamics. They have been used as powerful computational tools to solve complex pattern recognition, function estimation, and classification problems. ANNs have been evolving towards more powerful and more biologically realistic models. In the past decade, Spiking Neural… (More)

- Mehran Ahmadlou, Hojjat Adeli, Amir Adeli
- Clinical EEG and neuroscience
- 2012

This article presents a new methodology for investigation of the organization of the overall and hemispheric brain network of patients with attention-deficit hyperactivity disorder (ADHD) using theoretical analysis of a weighted graph with the goal of discovering how the brain topology is affected in such patients. The synchronization measure used is the… (More)