in recent years, wavelet packet modulation ofdm (wpm-ofdm) signals have been introduced for radar applications. these signals have important properties such as inherent high range resolution and high resistance of radar system against jamming reception. this paper investigates the problem of designing these family of signals according to the following criteria: constrained maximization of the d...

Here Θ : X → IR is a continuously differentiable mapping, X ⊆ IR is an open set containing the feasible region Ω and Ω is an n-dimensional box, Ω = {x ∈ IR : l ≤ x ≤ u}. These inequalities are meant component-wise and l ∈ (IR ∪−∞), u ∈ (IR ∪∞). Taking into account the variety of applications yielding the problem (1), we allow any relationship between m and n. The relevance of this problem is we...

In this paper, we propose modiications to a prototypical branch and bound algorithm for nonlinear optimization so that the algorithm eeciently handles constrained problems with constant bound constraints. The modiications involve treating subregions of the boundary identically to interior regions during the branch and bound process, but using reduced gradients for the interval Newton method. Th...

The paper presents and evaluates the power of a new framework for optimization in graphical models, based on AND/OR search spaces. The virtue of the AND/OR representation of the search space is that its size may be far smaller than that of a traditional OR representation. We develop our work on Constraint Optimization Problems (COP) and introduce a new generation of depth-first Branch-and-Bound...

The paper presents and evaluates the power of a new framework for constraint optimization, based on the concept of AND/OR search trees. The virtue of the AND/OR search tree representation is that its size may be smaller than that of a traditional OR search tree. We introduce a new generation of depth first Branch-and-Bound algorithms that traverse an AND/OR search space and use the Mini-Bucket ...

Decomposition is a powerful technique for reducing the size of a backtracking search tree. However, when solving constraint optimization problems (COP’s) the standard technique of invoking a separate recursion to solve each independent component can significantly reduce the strength of the bounds that can be applied when using branch and bound techniques. In this paper we present a new search a...

Many engineering problems can be cast as optimization problems subject to convex constraints that are parameterized by an uncertainty or 'instance' parameter. Two main approaches are generally available to tackle constrained optimization problems in presence of uncertainty: robust optimization and chance-constrained optimization. Robust optimization is a deterministic paradigm where one seeks a...