ROUND Approximate TTeMPS operator within a prescribed tolerance. X = ROUND( A, tol ) truncates the given TTeMPS operator A to a lower rank such that the error is in order of tol.

- TTeMPS
- round ROUND Approximate TTeMPS tensor within a prescribed tolerance.
- round ROUND Approximate TTeMPS tensor within a prescribed tolerance.
- round ROUND Approximate TTeMPS operator within a prescribed tolerance.

- elliptope_SDP Solver for semidefinite programs (SDP's) with unit diagonal constraints.
- elliptope_SDP_complex Solver for complex semidefinite programs (SDP's) with unit diagonal.
- low_rank_tensor_completion Given partial observation of a low rank tensor, attempts to complete it.
- low_rank_tensor_completion_TT Example file for the manifold encoded in fixedTTrankfactory.
- low_rank_tensor_completion_embedded Given partial observation of a low rank tensor (possibly including noise),
- realphasefactory Returns a manifold struct to optimize over phases of fft's of real signals
- essentialfactory Manifold structure to optimize over the space of essential matrices.
- TTeMPS_block
- round ROUND Approximate TTeMPS tensor within a prescribed tolerance.
- TTeMPS_op
- round ROUND Approximate TTeMPS operator within a prescribed tolerance.
- example TTeMPS Toolbox.
- trs_gep Solves trust-region subproblem with TRSgep in a subspace of tangent space.
- tangentorthobasis Returns an orthonormal basis of tangent vectors in the Manopt framework.

0001 function A = round(A, tol ) 0002 %ROUND Approximate TTeMPS operator within a prescribed tolerance. 0003 % X = ROUND( A, tol ) truncates the given TTeMPS operator A to a 0004 % lower rank such that the error is in order of tol. 0005 0006 % TTeMPS Toolbox. 0007 % Michael Steinlechner, 2013-2016 0008 % Questions and contact: michael.steinlechner@epfl.ch 0009 % BSD 2-clause license, see LICENSE.txt 0010 0011 C = cell(1, A.order); 0012 for i = 1:A.order 0013 C{i} = reshape(A.U{i}, [A.rank(i), A.size_col(i)*A.size_row(i), A.rank(i+1)]); 0014 end 0015 X = TTeMPS( C ); 0016 X = round(X, tol); 0017 for i = 1:A.order 0018 A.U{i} = reshape(X.U{i}, [X.rank(i), A.size_col(i), A.size_row(i), X.rank(i+1)]); 0019 end 0020 0021 A = update_properties(A); 0022 0023 end

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