Nonnegative sparse solutionThe problem of finding a sparse solution for linear equations has been investigated extensively in recent years. This is an NP-hard combinatorial problem, and one popular method is to relax such combinatorial requirement into an approximated convex problem, which can avoid ...
Why is a rectangle a convex set? How do you proof a function is convex? How do you determine if a set is convex? Do convex functions have only one minimizer? How to prove if a function is convex? How to prove that a function is convex? What is a convex non-linear problem? How ...
Although this problem is well defined when we select the best model, i.e., the model that has the least error, it is common to select the most parsimonious model instead of the best model in practice. Then, how do we determine the “most parsimonious model” from the results? This ...
This problem can be resolved by subdividing one of the offending curves so that Bézier curve convex hulls no longer overlap, as shown in Figure 25-6.Figure 25-6 Handling Overlapping Triangles We locally triangulate all non-overlapping Bézier convex hulls. For quadratics, the Bézier convex ...
Since the optimization problem (4) is non-convex, due to the stiffness-penalization, any gradient-based solution method will end up in a local minimum. To ensure high-quality designs (strong local minima), and to allow for a smooth and fast convergence, a continuation strategy is applied for...
In this paper we address the problem of building convenient criteria to solve linear and noisy inverse problems of the form y = Ax + n. Our approach is based on the specification of constraints on the solution x through its belonging to a given convex se
The real-time generation of fuel-optimal paths to a prescribed location on a planet's surface is a challenging problem due to the constraints on the fuel, the control inputs, and the states. The main difficulty in solving this constrained problem is the existence of nonconvex constraints on ...
If the problem has an equivalent convex optimization formulation with a computable objective function, a line search can be used to determine the weight applied to the alternative solution, referred to as the step size. In the absence of a convex optimization formulation, the typical approach is ...
Afeasibility problem, consisting of one or more constraints and no objective. Constraints¶ Three types of constraints may be specified in disciplined convex programs: Anequality constraint, constructed using==, where both sides are affine.
目标函数看上去确实是凸的，报这个错可能的原因：1. G(SH'H)^(-1)G'的计算错误导致成非半正定的...