Neonatal_seizure_detection

Automated seizure detection algorithm for neonatal EEG
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These C/C++ source files consist of 150 classes, 300,000 lines of code, excluding a Qt-based user interface. Its functionality includes: GLM-statistics, hierarchical clustering, (non)-linear optimization, L1 and L2 norm minimization, Hungarian algorithm, EEG/MEG forward and inverse modelling, Boundary Element Method, spatio/temporal covariance modelling, image fusion, triangular meshes, KD-trees, topological error correction, marching cubes & spherical triangulations, sparse matrices and matrix operations, spherical harmonics, wavelets, spectra and spectrograms, Fast Fourier transform (FFTWest), data import for many different EEG/MEG data formats, data import for many image data formats.
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