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@article{144538,
        author = {B Rajeswari and T Anil Raju},
        title = {Synchronization Likelihood - a Non Linear Multivariate Technique for finding Functional Connectivity},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {12},
        pages = {156-166},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144538},
        abstract = {The brain is a highly complex biological system. The study of complex systems requires the use of analytical tools which can detect statistical dependencies between time series recorded from the interacting subsystems. This work aims to study various signal processing methods to determine the functional connectivity in the brain using multichannel EEG signals. The functional connectivity is analyzed using linear and non linear techniques with correlation and synchronization Likelihood. Functional connection is obtained by computing the correlation among multi channel EEG data by applying different threshold. Coherency of EEG is sensitive only to linear and symmetric interdependencies and cannot deal with non-stationarity. The approach is based upon the theory of non­linear dynamical systems. This discusses the Synchronization Likelihood, a multivariate non­linear technique which measures synchronization between different brain sites.},
        keywords = {Synchronization Likelihood, Non-linear, Dynamical System},
        month = {},
        }