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Vahid Abootalebi
Also published under:V. Abootalebi
Affiliation
Electrical Engineering Department, Yazd University, Yazd, Iran
Topic
Graph Laplacian,Graph Signal,Laplacian Matrix,EEG Data,EEG Signals,Motor Imagery,Motor Imagery Tasks,Signal Processing,Smoothing,Brain Connectivity,Brain Fingerprinting,Brain-computer Interface System,Chebyshev Polynomials,Classification Accuracy,Computational Complexity,Diagonal Matrix,Discriminative Features,Discriminative Subspace,EEG Graph,Edge Weights,Eigenvalues Of The Laplacian Matrix,End Of The Spectrum,Epoch Length,Eyes Open,Frequency Band,Frobenius Norm,Functional Connectome,Graph Learning,Graph Partitioning,Graph Size,Graph Structure,Hand Foot,Heat Kernel,Imagery Task,Large Graphs,Linear Combination,Low-pass,Magnetoencephalography,Motor Activity,Neuroimaging,Neuroimaging Modalities,Nodes In The Graph,Noisy Signal,Pearson Correlation,Polynomial Of Degree,Rapid Fluctuations,Regularization Parameter,Remainder Of This Paper,Research In Recent Years,Rest Of The Trial,
Biography
Vahid Abootalebi received the BS and MS degrees in electrical engineering from the Sharif University of Technology, Tehran, Iran, in 1997 and 2000, respectively, and the PhD degree in biomedical engineering from the Amirkabir University of Technology, Tehran, Iran in 2006. Since 2007, he has been working as a faculty member of the Electrical Engineering Department of Yazd University, where he is currently an associate professor. His main research interests include biomedical signal processing and pattern recognition.