The SVDL method computes a partial, approximate SVD decomposition of a general linear operator
svdl
The implementation of thick restarting follows closely that of SLEPc as described in 1. Thick restarting can be turned off by setting k = maxiter, but most of the time this is not desirable.
The singular vectors are computed directly by forming the Ritz vectors from the product of the Lanczos vectors L.P/L.Q and the singular vectors of L.B. Additional accuracy in the singular triples can be obtained using inverse iteration.
A deterministic seed is used for generating pseudo-random initial
data for the algorithm; this can be controlled by passing a
different pseudorandom number generator (an AbstractRNG) via
the rng keyword argument, or by passing an initial v0 vector
directly.
Footnotes
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Vicente Hernández, José E. Román, and Andrés Tomás. "A robust and efficient parallel SVD solver based on restarted Lanczos bidiagonalization." Electronic Transactions on Numerical Analysis 31 (2008): 68-85. ↩