A Novel Flexible Model for the Extraction of Features from Brain Signals in the Time-Frequency Domain

<table>Flow chart of the fitting process. Initial parameters are derived from the TFR data, or a previously fitted model is used to determine <svg height="13.3" id="M123" style="vertical-align:-3.50804pt" version="1.1" viewbox="0 0 10.2 13.3" width="10.2" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg>. The model is fitted using a nonlinear optimization algorithm. If desired, the optimal model can be iteratively refined up to <svg height="15.4" id="M124" style="vertical-align:-3.3907pt" version="1.1" viewbox="0 0 36.512501 15.4" width="36.512501" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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International Journal of Biomedical Imaging

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Figure 4

Figure 4: A Novel Flexible Model for the Extraction of Features from Brain Signals in the Time-Frequency Domain 