搜索资源列表
program
- 目标函数是De Jong函数，是一个连续、凸起的单峰函数-Objective function is De Jong function, is a continuous, convex function of the single-peak
tuhanshu
- 详细的介绍了凸函数的一阶范数最优解问题,并且给出一实例-Detailed account of the convex function of the first-order optimal solution norm, and gives an example
1
- 用C 语言实现的对于凸包问题的求解。实现了基本的功能，代码量很少采用插值算法，先生成四个原始点，之后判断其他点-Using C language for the convex hull of the solution of the problem. To achieve the basic function of the volume of rarely used code interpolation algorithm, the original Mr. into four points, a
GTPSO
- 提出一种改进的粒子群优化算法———基于全局劣汰策略的混合粒子群优化算法(GTPSO) 。GTPSO在 保持PSO算法快速收敛的基础上,以郭涛算法(GuoA)的寻优机制确保种群的多样性和算法的坚韧性。数值计 算结果表明,对于高维(维数≥10)复杂非凸多峰函数的数值优化问题, GTPSO算法的计算结果均优于GuoA算 法和粒子群优化算法。-An improved particle swarm optimization algorithm--- poor overall survival
graham
- 构造凸包接口函数,传入原始点集大小n,点集p(p原有顺序被打乱!),返回凸包大小,凸包的点在convex中-Construct convex hull interface function, introduced the original point set size n, the point set p (p the original order has been disrupted!), Returns the size of the convex hull, convex hull of
Optimal
- 几个凸优化函数，用于解决非约束和带约束条件的凸优化问题-Several convex optimization function, for solving non-binding and the constrained convex optimization problem
tuxing
- 输入N个点的坐标，判断这N个点能否构成一个凸多边形。功能简单明了.-Enter the coordinates of N points to determine whether these N points form a convex polygon. Function simple.
Convexoptimization
- methods of convex function optimization
equalizer_design
- Designs a frequency-domain and time-domain FIR equalizer for a single-input single-output (SISO) channel. Frequency-domain equalization uses a Chebychev criteria and is specified in terms of frequency response functions. It is a conv
fir_chebychev_design
- Designs an FIR filter given a desired frequency response H_des(w). The design is judged by the maximum absolute error (Chebychev norm). This is a convex problem (after sampling it can be formulated as an SOCP). minimize max |H(w) - H_de
fir_lin_phase_lowpass_max_atten
- Designs a linear phase FIR lowpass filter such that it: - minimizes maximum stopband attenuation - has a constraint on the maximum passband ripple This is a convex problem (when sampled it can be represented as an LP). minimize m
Rosenbrock
- The Rosenbrock function is a non-convex function used as a performance test problem for optimization algorithms introduced by Rosenbrock (1960). It is also known as Rosenbrock s valley or Rosenbrock s banana function. The global minimum is insid
Convex-Optimization-
- 一本很好的凸优化书，有助于进一步学习凸函数及优化理论。-A good book convex optimization, convex function and help to further study and optimization theory.
xxl
- 平均互信息是信源概率的上凸函数,是信道概率的下凸函数,该软件展示他们平面图与三维可视图.直观.-The average mutual information source probability convex function, convex function of the probability of channel, the software shows they plan and 3D view. Intuitive.
Convex-optimization
- “凸优化” 是指目标函数为凸函数且由约束条件得到的定义域为凸集的优化问题。文章是MIT的公开课讲义。-"Convex optimization" refers to the objective function is convex function and the constraint conditions are the domain of optimization problem for convex set. Article is MIT public class notes.
GAalgorithm
- 遗传算法求解非凸函数的极值，包含选择交叉变异子函数-Using Genetic algorithm to solve the extremum of non-convex function
Banana-Function-Convex-Optimization
- 优化的Banana函数-各类优化方法的对比-Banana optimization function- Comparison of various types of optimization methods
optimization-algorithm
- 在运筹学基础中，有讲解许多算法，在实际中也会用的到，在这编了几个程序，有凸函数、加布探索法、牛顿法，多数情况下是通用的，只需改几个参数，换下函数即可。-In Operations Research Foundation, there are many algorithms to explain which will be used to do something in practice.There are series of few procedures, including convex f
GMC_software
- 用于稀疏优化的最新非凸函数GMC算法，可用于信号处理以及图像处理。(The latest non convex function GMC algorithm for sparse optimization, can be used for signal processing and image processing.)
PSO
- 梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commo