A data-driven reconstruction recovers leading resonant normal form coefficients in phase oscillator networks from noisy observations, with first- and second-order procedures and proven error bounds under stated assumptions.
On the phase reduc- tion and response dynamics of neural oscillator populations.Neural Computation, 16(4):673–715, April 2004
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Reconstructing resonant phase oscillator interactions from noisy time series
A data-driven reconstruction recovers leading resonant normal form coefficients in phase oscillator networks from noisy observations, with first- and second-order procedures and proven error bounds under stated assumptions.