Description: A hybrid Particle Swarm Optimization algorithm for finding the minimum of
the function fitness in the real space.-Particle Swarm Optimization algo abbreviation for finding the minimum of the function fi tness in the real space. Platform: |
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Author:chen |
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Description: 1.功能
用高斯方法计算n重积分(C语言)
2.参数说明
int n : 积分重数
int js[n] : js[k]表示第k层积分区间所划分的子区间
void (*ss)() : 指向计算各层积分上、下限的函数名(用户自编)
double (*f)() : 指向计算被积函数值的函数名(用户自编)
double gaus() : 函数返回积分值
3.文件说明
gaus.c为函数程序
gaus0.c为主函数程序-1. Gaussian function method using n-integration (C) 2. Note int n parameters : Integral focus on the following int js [n] : js [k] said k-interval division of subinterval void (* ss) () : at all levels of integral calculation of the maximum and minimum levels of function (user wrote) double (* f) () : plot at the function were calculated value of the function (user wrote) double gaus () : function returns three integral values. This document explains procedures gaus.c to function mainly function procedures gaus0.c Platform: |
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Author:罗坤 |
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Description: 把各阶导函数的ESD作为a的函数，确定其峰值频率的数值。该函数把以下变量作为输入：a的最小值alphamin，其增量步长alphastep；-various derivative function of the ESD as a function of its peak frequency values. The function of the following variables as input : a minimum of alphamin. its incremental step alphastep; Platform: |
Size: 1636 |
Author:meimei |
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Description: 估算并画出高斯脉冲的前15阶导函数的-10dB带宽。函数以下列变量为输入：a的最小值alphamin，-estimates and the mapping out of the Gaussian pulse before 15 derivative function-10dB bandwidth. Function for the importation of the following variables : a minimum of alphamin. Platform: |
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Author:meimei |
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Description: BNB20 Finds the constrained minimum of a function of several possibly integer variables.
％ Usage: [errmsg,Z,X,t,c,fail] =
％ BNB20(fun,x0,xstatus,xlb,xub,A,B,Aeq,Beq,nonlcon,settings,options,P1,P2,...)
％
％ BNB solves problems of the form:
％ Minimize F(x) subject to: xlb <= x0 <=xub
％ A*x <= B Aeq*x=Beq
％ C(x)<=0 Ceq(x)=0
％ x(i) is continuous for xstatus(i)=0
％ x(i) integer for xstatus(i)= 1
％ x(i) fixed for xstatus(i)=2
％-BNB20 Finds the constrained minimum of a fu nction of several possibly integer variables. % Usage : [errmsg, Z, X, t, c, fail] =% BNB20 (fun, x0, xstatus, xlb, xub, A, B, Aeq, Beq, nonlcon. settings, options, P1, P2, ...)%% BNB solves problems of the form : Minimize% F (x) subject to : xlb Platform: |
Size: 6683 |
Author:冯颖 |
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Description: blog
又搭工，又打料，几天几宿没睡觉！也挺累的！
增加了系统设置菜单，在此菜单里可以更改回复计划密码，博主图片以及网站顶部的图片。另外博客最低部的说明文字也可以在这里进行修改。在计划管理上，增加了两个菜单，网友可以对你的计划回复进行评价了。另外就是改进了分页功能。 自我感觉这套应该是比较完善的一套。尽管花了很多努力，难免也有不足之出，希望各位兄台能不吝提出来。共同学习，花同进步。
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发文章之前，先加上分类！-blog also take workmanship is expected to fight a few days, not a few places to sleep! Also refreshing! Increase the system set up menu, the menu they can change passwords response plan, Mr. main website of pictures and the top of the picture. Another blog minimum of explanatory text can be amended here. Management of the scheme, an increase of two menu, netizens can you plan to evaluate the response. The other is to improve the paging function. This sense of self, it should be a more perfect one. Despite spent a lot of efforts, it is inevitable that there are deficiencies that hope you will not hesitate to Kuangyi raised. Learning together with the flower progress. Contact : 278274384, or : MSX : wangjinbo589@hotmail.com eMail : wangjinbo589@126.com. Otherwise, on the previous http : Platform: |
Size: 593564 |
Author:sigo |
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Description: 使用遗传算法求函数的极小值的一个例子，使用遗传算法求函数的极小值的一个例子-the use of genetic algorithms to find the minimum value function of an example, the use of genetic algorithms to find the minimum value function of an example Platform: |
Size: 1070 |
Author:J.K.Wang |
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Description: 使用遗传算法求函数的极小值的一个例子，使用遗传算法求函数的极小值的一个例子-the use of genetic algorithms to find the minimum value function of an example, the use of genetic algorithms to find the minimum value function of an example Platform: |
Size: 1024 |
Author:J.K.Wang |
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Description: 自适应遗传算法 求解函数最小值，在MATLAB环境下-Adaptive Genetic Algorithm for the minimum function in the MATLAB environment Platform: |
Size: 38912 |
Author:邵斓 |
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Description: The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order -The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order Platform: |
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Author:kedle |
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Description: 用BP网络建立映射关系，为遗传算法提供适应度函数，通过改进遗传算法完成最小值优化-the mapped relation is built using BP network in order to provide fitness function for genetic algorithm. At last, optimization of minimum value is finished by genetic algorithm. Platform: |
Size: 1024 |
Author:wangchanglong |
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Description: This a demonstration of how to find a minimum of a non-smooth
objective function using the Genetic Algorithm (GA) function in the
Genetic Algorithm and Direct Search Toolbox. Traditional derivative-based
optimization methods, like those found in the Optimization Toolbox, are
fast and accurate for many types of optimization problems. These methods
are designed to solve smooth , i.e., continuous and differentiable,
minimization problems, as they use derivatives to determine the direction
of descent. While using derivatives makes these methods fast and
accurate, they often are not effective when problems lack smoothness,
e.g., problems with discontinuous, non-differentiable, or stochastic
objective functions. When faced with solving such non-smooth problems,
methods like the genetic algorithm or the more recently developed pattern
search methods, both found in the Genetic Algorithm and Direct Search
Toolbox, are effective alternatives. -This is a demonstration of how to find a minimum of a non-smooth
objective function using the Genetic Algorithm (GA) function in the
Genetic Algorithm and Direct Search Toolbox. Traditional derivative-based
optimization methods, like those found in the Optimization Toolbox, are
fast and accurate for many types of optimization problems. These methods
are designed to solve smooth , i.e., continuous and differentiable,
minimization problems, as they use derivatives to determine the direction
of descent. While using derivatives makes these methods fast and
accurate, they often are not effective when problems lack smoothness,
e.g., problems with discontinuous, non-differentiable, or stochastic
objective functions. When faced with solving such non-smooth problems,
methods like the genetic algorithm or the more recently developed pattern
search methods, both found in the Genetic Algorithm and Direct Search
Toolbox, are effective alternatives. Platform: |
Size: 18432 |
Author:gao |
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Description: -least squares algorithms using gradient descent
to find minimum of function
- gaussian fit algorithm
Platform: |
Size: 1024 |
Author:mic |
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Description: 舞蹈链变种，估价函数，选择一个未被控制的列，很明显该列最少需要1个行来控制，所以我把ret++。该列被控制后，我把它所对应的行，全部设为已经选择，并把这些行对应的列也设为被控制。继续选择未被控制的列，直到没有这样的列。-The dance chain variants, the valuation function, select a column not control, it is clear that column requires a minimum of a line of control, the I ret++. The column control to the corresponding row, all set to have chosen, and the corresponding column of these rows is also set to be controlled. The continue selecting Uncontrolled column is, until no such a column. Platform: |
Size: 1024 |
Author:陶翔 |
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Description: 通过例子讲解模拟退火法的优化原理和方法，浅显易懂！-The global minimum of function can be obtained by the simulated annealing algritm. Platform: |
Size: 1024 |
Author:GX |
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Search - minimum of function