ConvexOptimization
class boulderopal.noise_reconstruction.ConvexOptimization(power_density_lower_bound, power_density_upper_bound, regularization_hyperparameter)
Configuration for noise reconstruction with the convex optimization (CVX) method.
Parameters
- power_density_lower_bound (float) – The lower bound for the reconstructed power spectral densities. It must be greater than or equal to 0.
- power_density_upper_bound (float) – The upper bound for the reconstructed power spectral densities. It must be greater than the power_density_lower_bound.
- regularization_hyperparameter (float) – The regularization hyperparameter
Notes
The CVX method finds the estimation of the power spectral density (PSD) matrix
where is the matrix of weighted filter functions and denotes the Euclidean norm and
is a positive regularization hyperparameter which determines the smoothness of