cheap_norm.m

The cheapest norm for various representations of matrices. CUDA stores matrices by rows, Matlab by columns, and polyadic objects can only multiply vectors, in which case Algorithm 2.4 from Higham and Tisseur's paper (https://doi.org/10.1137/S0895479899356080) is used.

Syntax

    n=cheap_norm(A,t,itmax)

Parameters

    A     - a matrix, or a polyadic representation thereof

    t     - (optional) number of probe columns in the poly-
            adic norm estimator, defaults to 1

    itmax - (optional) maximum number of estimator iterati-
            ons, defaults to 5

Outputs

    n - infinity-norm for GPU arrays, 1-norm for CPU arrays,
        and a lower-bound 1-norm estimate for polyadics

Notes

Some norms are vastly more expensive than others; this function uses the cheapest ones available.

See also

clean_up.m, frob_chop.m, hdot.m, mprealloc.m, acomm.m, arnoldi.m, atranspose.m, aux_mat.m, binpack.m, cheb_coeff.m, dirdiff.m, eigenfields.m, expdrop.m, expmint.m, expmint2.m, fftdiff.m, fourdif.m, fourlap.m, gaussfun.m, herm_spline.m, jacobianest.m, keep_rank.m, krondelta.m, kronm_new.m, logfactorial.m, lorentzcon.m, lorentzfun.m, md5_hash.m, remncomm.m, remtrace.m, rspert.m, rspt_eig.m, snormpdf.m, svd_shrink.m, tikhoind.m, tikhonov.m, trapdiff.m, unit_oper.m, unit_state.m, vvpert.m, Kernel_utilities

Version 2.3, authors: Ilya Kuprov