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LS experiments—2 overlapping processes, 7/11/2004

LS experiments—2 overlapping processes, 7/11/2004. In noise-free case, perfect estimates for both processes. Visually, it is hard to verify convergence when the number of trials increases in the presence of noise in the data.

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LS experiments—2 overlapping processes, 7/11/2004

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  1. LS experiments—2 overlapping processes, 7/11/2004 • In noise-free case, perfect estimates for both processes. • Visually, it is hard to verify convergence when the number of trials increases in the presence of noise in the data.

  2. OLS learns 2 processes, overlapping in time, 1 voxel, zero noise, start times known, 5 trials Estimates: -0 0.25 0.5 0.75 1 0.75 0.5 0.25 4.9651e-17 9.3095e-17 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5

  3. OLS learns 2 processes, overlapping in time, 1 voxel, zero noise, start times known, 10 trials Estimates: -0 0.25 0.5 0.75 1 0.75 0.5 0.25 3.5108e-17 -4.7535e-17 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5

  4. OLS learns 2 processes, overlapping in time, 1 voxel, noise 0.2, start times known, 5 trials Estimates: 0.094915 0.26407 0.42792 0.7071 1.0337 0.81342 0.59745 0.42883 -0.048884 -0.17886 0.73122 0.22735 0.56561 0.52506 0.53043 0.43789 0.59811 0.51577

  5. OLS learns 2 processes, overlapping in time, 1 voxel, noise 0.2, start times known, 10 trials Estimates: 0.0054956 0.32446 0.48847 0.83317 0.99872 0.86555 0.55624 0.23633 -0.050592 -0.017376 0.36435 0.36134 0.4856 0.60143 0.46168 0.54137 0.47466 0.52419

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