Convex optimization descent, and nonsmooth filter methods. Solving even close-to-convex but non-convex problems can be computationally intractable. Minimizing a unimodal function is intractable, regardless of the smoothness of the function, according to results of Ivanov. Conventionally, the definition of the convex optimization problem (we recall) requires that the objective function "f" to be "minimized" and the feasible set be convex. In the special case of linear programming (LP), the objective function is both concave and convex, and so LP can also consider the problem of maximizing an objective function without confusion. However, for most convex minimization problems, the objective function is not
Telecentric lens (or "collimated") illuminators, which produce a parallel light flow, often from LED sources. An image-space (or image-side) telecentric lens produces images of the same size regardless of the distance between the lens and the film or image sensor. This allows the lens to be focused to different distances without changing the size of the image. Image-space telecentric lenses have an exit pupil infinitely far in front of the lens; that is, if one looks in the back of the lens, the image of the aperture is very far away. At the film or image sensor, all of the chief rays