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@article{144438,
        author = {B Rajeswari and T. Anil Raju},
        title = {Wavelet Entropy Measure to Quantify Information Transmission using EEG Signals },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {11},
        pages = {167-173},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144438},
        abstract = {The electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of brain dynamics. These current waveforms were decomposed using wavelet analysis into different approximation and details. The wavelet entropy of such decompositions is analyzed reaching a successful methodology for information transmission. The suggested approach is tested using different event related potentials (ERP) conditions and different types of cognitive disorders are proven successful identification for the transmission of information.},
        keywords = {EEG, Mutual Information transmission, Wavelet Entropy},
        month = {},
        }