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    Numerical versus analytic synchronization in small-world networks of hindmarsh-rose neurons

    , Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1 December 2009 through 1 December 2009, Melbourne, VIC ; Volume 5866 LNAI , 2009 , Pages 627-635 ; 03029743 (ISSN) ; 364210438X (ISBN) Jalili, M ; Sharif University of Technology
    Abstract
    Neuronal temporal synchronization is one of the key issues in studying binding phenomenon in neural systems. In this paper we consider identical Hindmarsh-Rose neurons coupled over Newman-Watts small-world networks and investigate to what extent the numerical and analytic synchronizing coupling strengths are different. We use the master-stability-function approach to determine the unified coupling strength necessary for analytic synchronization. We also solve the network's differential equations numerically and track the synchronization error and consequently determine the numerical synchronizing coupling parameters. Then, we compare these two values and investigate the influence of various... 

    Multivariate Synchronization Analysis of Brain Electroencephalography Signals: A Review of Two Methods

    , Article Cognitive Computation ; Volume 7, Issue 1 , February , 2013 , Pages 3-10 ; 18669956 (ISSN) Jalili, M ; Sharif University of Technology
    Springer New York LLC  2013
    Abstract
    Temporal synchronization of neuronal activity plays an important role in various brain functions such as binding, cognition, information processing, and computation. Patients suffering from disorders such as Alzheimer’s disease or schizophrenia show abnormality in the synchronization patterns. Electroencephalography (EEG) is a cheap, non-invasive, and easy-to-use method with fine temporal resolution. Modern multichannel EEG data are increasingly being used in brain studies. Traditional approaches for identifying synchronous activity in EEG are through univariate techniques such as power spectral density or bivariate techniques such as coherence. In this paper, we review two methods for... 

    How to synchronize and register an optical-inertial tracking system

    , Article Applied Mechanics and Materials ; Volume 332 , 2013 , Pages 130-136 ; 16609336 (ISSN) ; 9783037857335 (ISBN) Soroush, A ; Akbar, M ; Farahmand, F ; Sharif University of Technology
    2013
    Abstract
    Multi-sensor tracking is widely used for augmentation of tracking accuracy using data fusion. A basic requirement for such applications is the real time temporal synchronization and spatial registration of two sensory data. In this study a new method for time and space coordination of two tracking sensor measurements has been presented. For spatial registration we used a body coordinate system and then applied the effect of the level arm. The time synchronization was done based on least mean square (LMS) error method. This method was implemented to synchronize the position and orientation of an object using Inertial (1IMU) and Optical (Optotrak) tracking systems. The results of synchronized...