Convex operators via optimization (OPT), Kernel average
[y, argmin] = opt_ka(f1, df1, domf1, f2, df2, domf2, g, dg, domg, x, lambda, output)
Univariate functions, continuous but (potentially) nonsmooth.
Univariate functions: derivatives of f1, f2, g (respectively).
Domains of functions f1, f2, g (set of points where function is finite). Domains are stored as intervals I=[lb,ub] with ub<lb storing an empty set.
Vector of points at which to evaluate the kernel average.
real number. lambda1 = 1 - lambda. lambda2 = lambda.
0: no output, 1: progress bar.
The values of the kernel average evaluated at x.
A point at which the kernel average attains its minimum, for each x.
Computes the (kernel average) g-average of f1 and f2 evaluated on vector x, giving the values y such that