or a messed up CVX installation, or due to a CVX rules violation. You haven’t shown the complete program, so I don’t know whether all the arguments on the LHS of the exponential(1) constraint are affine, as they must be.
numerator = cvx real affine expression (scalar) 1 Like Why can't the code run if i just modify some variable and formula?11119 (蕭仰恩) February 15, 2019, 12:19am 5 i know where is difference,the original formula is |f_k|^2,but i rewrite the code as F_k,because the ...
In disciplined convex programming, a scalar expression is classified by itscurvature. There are four categories of curvature:constant,affine,convex, andconcave. For a function\(f:\mathbf{R}^n\rightarrow\mathbf{R}\)defined on all\(\mathbf{R}^n\), the categories have the following meanings: ...
A CVX expression can be multiplied or divided by a scalar constant. If the constant is positive, the curvature is preserved; if it is negative, curvature is reversed. An affine column vector CVX expression can be multiplied by a constant matrix of appropriate dimensions; or it can be left-...
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a valid constant or affine expression; a valid call to a function in the atom library with a convex result; an affine scalar raised to a constant power p\geq 1, p\neq3,5,7,9,...; a convex scalar quadratic form---see :ref:`quadforms`; the sum of two or more convex expressions...
The vector sk contains :cvx convex expression (scalar),cvx zero constant expression (scalar),and cvx real affine expression (scalar). I use this expression for constraint (39b): norm(s_k(k,:))<=G_k(:,k).’*v_k(:,k); however, matlab told me that“Disciplined convex programming erro...
specification, assuming x is a vector optimization variable, A is a matrix, b and c are vectors, and d is a scalar. CVX recognizes this objective expression as a convex function, since it is the composition of a convex function (the quadratic-over-linear function) with an affine function....
" Cannot perform the operation: {real affine} .* {convex}" I found rare posts related to nested/embeded/multi-level convex optimization and the DCP rule sets seem a little tricky for me currently. Could anyone can help me figure out this problems? Please let me know if...
Two CVX expressions can be added together if they are of the same dimension (or one is scalar) and have the same curvature (i.e., both are convex, concave, or affine). A CVX expression can be multiplied or divided by a scalar constant. If the constant is positive, the curvature is ...