搜索资源列表
Trust-Region
- 用BFGS更新矩阵的信赖域法解优化问题的MATLAB程序-Trust Region Method For Solving Optimization Problem
Variable-Scale-method
- 变尺度法BFGS算法的C++源码,解优化问题。-C++ code for variable scale method BFGS algorithm, solve optimized problems.
se22
- 一类非单调保守BFGS算法研究.A class of Nonmonotone conserved BFGS algorithm.-A class of Nonmonotone conserved BFGS algorithm.
Newton-method-
- 用牛顿法，最速下降法，BFGS公式求解同一问题，并可比较其收敛速度-With Newton method, the steepest descent method, BFGS formula to solve the same problem , and can compare the convergence speed
fminlbfgs_version2
- 可以实现大规模的bfgs功能，进行目标函数的最优化求解，即L-BFGS-Can achieve large scale bfgs function, the objective function is the most optimal solution, ie, L-BFGS
liblbfgs
- 一个有限内存Broyden-Fletcher-Goldfarb-Shanno函数半二次优化工具，可以用来进行求解函数最优值。-libLBFGS is a C port of the implementation of Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, which can be used to solve the optimization
hucrf_code
- Hidden-Unit Conditional Random Fields 工具箱，可以用于训练linearCRF和和L.J.P. van der Maaten, M. Welling 提出的huCRF-We provide Matlab code that implements the training and evaluation of hidden-unit CRFs, as well as code to reproduce the results of our experim
Array-beamforming-optimization
- 本文给出了一种利用幅相加权对阵列天线进行全局优化的方法。为了使天线的辐射波束形成给定的 方向图，采用联合应用DFP和BFGS公式的变度量算法对阵列天线各单元的馈电幅度和相位分布进行优化， 通过C++语言编程计算实现，从而使得优化后的阵列天线主波束形状能够与预给波束形状相吻合，达到设计 要求。全局优化是本文的特色，它弥补了局部优化结果的精确度依赖于初始值的缺点，因而得以保证通过优 化得到的天线主波束与给定波束的主瓣相吻合，副瓣也得到有效控制。该方法具有快速收敛，计算量小等优 点
wolfe-type-stepsize-search
- bfgs算法中需要用到的步长规则-the BFGS method
BBFGSF
- 利用BFGS算法求解大规模无约束最优化化问题，代码所用语言为Fortran77. -BFGS algorithm for solving large-scale unconstrained optimization of the problem, the code language used is Fortran 77.
DFP
- DFP算法是变尺度优化算法，使用唯相位的方法实现阵列天线的波束赋形状，是使用基于DFP和BFGS 变尺度优化算法来实现求值-DFP algorithm is to change the scale optimization algorithm, the use of CD-phase array antenna beamforming shape, is to use the scale variable based on the DFP and BFGS optimization algori
Optimization-GradientBase
- Sample code for optimization based on Gradient base. include BFGS, Steepest Descent method, DFP method, Conjugate Gradient method ans so on-Sample code for optimization based on Gradient base. include BFGS, Steepest Descent method, DFP method, Conjug
Quasi-Newton-Methods
- 拟牛顿法(Quasi-Newton Methods)是求解非线性优化问题最有效的方法之一。其实DFP算法、BFGS算法都属于拟牛顿法，即，DFP、BFGS都分别是一种拟牛顿法-Quasi-Newton method (Quasi-Newton Methods) is one of the most effective methods for solving nonlinear optimization problems. In fact, the DFP algorithm, BFGS algo
multidimensional-extremum-problems
- 无约束多维极值问题，包含 用模式搜索法求解多维函数的极值 用Rosenbrock法求解多维函数的极值 用单纯形搜索法求解多维函数的极值 用Powell法求解多维函数的极值 用最速下降法求解多维函数的极值 用共轭梯度法求解多维函数的极 用牛顿法求解多维函数的极值 用修正牛顿法求解多维函数的极值 用DFP法求解多维函数的极值 用BFGS法求解多维函数的极值 用信赖域法求解多维函数的极值 用显式最速下降法求正定二次函数的极值 -Unconstrain
Quasi-Newton
- 拟牛顿算法中的经典BFGS校正算法和DFP算法的matlab实验代码，broyden族算法的matlab程序。-Proposed Newton the classic algorithm the BFGS correction algorithm and DFP algorithm matlab experimental code, broyden family, algorithm matlab program.
Mutual_Information
- 研究了基于互信息测度的医学图像配准方法,提出了一种优化算法的改进。目的旨在于解决配准的精度和在基于互信息配准过程中的效率问题。提出的优化算法是将拟牛顿方法运用于多模医学图像配准中。实验结果说明这种改进的方法能有效提高配准的精度和效率问题,并得到好的实验效果。-Abstract: This paper presents a novel Optimized method for medical image registration, the purpose is to solve problems,
CRFtools.zip
- CRFsuite: a fast implementation of Conditional Random Fields (CRFs) CRFSuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. The first priority of this software is to train and use CRF models as fast as possi
ADL32-Lecture03-Report1.rar
- CRFsuite: a fast implementation of Conditional Random Fields (CRFs) CRFSuite is an implementation of Conditional Random Fields (CRFs) for labeling sequential data. The first priority of this software is to train and use CRF models as fast as possi
Lbfgsb.3.0.tar
- 无约束优化中非常有用的L-BFGS代码,在解决大规模优化问题中,有着良好的数值表现.-useful unconstrained optimization L-BFGS code, in the solution of large-scale optimization problems, has a good numerical performance.
MATLAB
- 这是BFGS方法解无约束优化的程序，使用方便，代码简单。-BFGS method for unconstrained optimization program, easy to use, simple code.