Docstrings
CalculateSampling(in)

Calculate the sampling operator of an n-dimension input. The output has the same size as the input.

Conjugate Gradients following Algorithm 2 from Scales, 1987. The user provides an array of linear operators. Verify that linear operator(s) pass the dot product. See also: DotTest

Arguments

• Niter=10 : Number of iterations
• mu=0
• tol=1.0e-15
DampRR.DotTestMethod.
DotTest(m_rand,d_rand,operators,parameters)

DampRR.FISTAMethod.
FISTA(x0,y,Hop,PARAM,mu,Nit)

FISTA: Solves the l2-l1 problem via Fast Iterative Shrinkage-Thresholdng Algorithm Given a linear operator H and it's adjoint H', the algorithm minimizes J = ||H x - y||2^2 + mu ||x||1, where H is the linear operator encapsulated in Hop

Arguments

• y:data
• Hop:linear operator
• PARAM:parameters to run Hop and it's adjoint
• x0:initial sol just to get size of x

Reference: Beck and Teboulle, 2009, A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems∗ SIAM J. Imaging Science, Vol 2 (1), 183-202

DampRR.IRLSMethod.
IRLS(d,operators,parameters;<keyword arguments>)

Non-quadratic regularization with Iteratively Reweighted Least Squares (IRLS).

Arguments

• Niter_external=3
• 'Niter_internal=10'
• mu=0
DampRR.SeisPOCSMethod.
SeisPOCS(in;<keyword arguments>)

Projection Onto Convex Sets interpolation of seismic records.

Arguments

• in: input data that can have up to 5 dimensions. Time is in the first dimension.
• p=1. : exponent for thresholding (1 is equivalent to soft thres. high number is equivalent to hard thresholding)
• alpha=1 : add-back ratio for imputation step. Use 1 for noise free data, and < 1 for denoising of original traces.
• dt=0.001 : sampling rate along the time axis (in seconds)
• fmax=99999. : maximum temporal frequency to process.