In many engineering applications it is common to find optimization problems where the cost function and/or constraints require complex simulations. Though it is often, but not always, theoretically possible in these cases to extract derivative information efficiently, the associated implementation procedures are typically non-trivial and time-consuming (e.g., adjoint-based methodologies). Deriv...

Derivative free optimization (DFO) methods are typically designed to solve optimization problems whose objective function is computed by a “black box”; hence, the gradient computation is unavailable. Each call to the “black box” is often expensive, so estimating derivatives by finite differences may be prohibitively costly. Finally, the objective function value may be computed with some noise, ...

The Savitzky–Golay (SG) filters are generally used for smoothing and differentiation in many fields. The properties of the SG smoothing filters have been well studied. However, the properties of the SG differentiation filters or SG digital differentiators (SGDD, for the first order differentiation) are not developed well somehow, although they have been widely used. In the paper, the properties...

Medical volume images contain ambiguous and low-contrast boundaries around which existing fullyor semiautomatic segmentation algorithms often cause errors. In this paper, we propose a novel system for intuitively and efficiently refining medical volume segmentation by modifying multiple curved contours. Starting with segmentation data obtained using any existing algorithm, the user places a thr...