non-convex optimization

基本解释

Many scientific, engineering and economic areas involve the optimization of complex, nonlinear and possibly non-convex problems.
科学领域，工程领域和经济领域都涉及到很多复杂的、非线性的甚至非凸形式的最优化问题。
When a non-conic convex optimization problem or its dual was infeasible, we considered the feasibility for the new system by introducing a concept of feasible distance.
当一般的非锥凸最优化问题或其对偶不可行时，通过引入可行距离这一概念，讨论新系统的可行性，并考察了在新系统中可行距离的性质，得到了与其等价的可计算的优化形式。
Due to the non-convex of the prior function and hyper-parameters, we use the dynamic posterior simulation rather than the general optimization methods to get reconstruction image.
由于采用的先验函数是非凸的并包含超验参数，一般的优化方法难以处理，采用动态后验模拟的方法可以很好地解决这些问题。