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NEURAL+NETWORK
- bp神经网络算法是解决最优化问题的先进算法之一，本论文讨论了神经网络中使用最为广泛的前馈神经网络。其网络权值学习算法中影响最大的就是误差反向传播算法（back-propagation简称BP算法）。BP算法存在局部极小点，收敛速度慢等缺点。基于优化理论的Levenberg-Marquardt算法忽略了二阶项。该文讨论当误差不为零或者不为线性函数即二阶项S(W)不能忽略时的Hesse矩阵的近似计算，进而训练网络。
levmar-2.4
- A sparse variant of the Levenberg-Marquardt algorithm implemented by levmar has been applied to bundle adjustment, a computer vision/photogrammetry problem that typically involves several thousand variables
LMprocess
- Levenberg-Marquardt优化-Levenberg-Marquardt optimization
OptimizationSample1
- Golden section method and Levenberg-Markardy method
Levenberg_Marquardt
- Levenberg Marquardt最优化算法.-the Optimization algorithm of Levenberg Marquardt.
Levenberg-Marquardt
- 上传的是Levenberg-Marquardt方法的基本原理-Upload is the basic principle of the Levenberg-Marquardt method
LM
- 上传的是Levenberg-Marquardt算法的Matlab程序-Upload is the Levenberg-Marquardt algorithm in Matlab
neuralmpc2
- Neural Predictive Control using Levenberg Marquard Optimization (Newton Method)
strapdown
- LM算法的MATLAB实现。Levenberg-Marquardt算法是最优化算法中的一种。最优化是寻找使得函数值最小的参数向量。-LM algorithm in MATLAB. Levenberg-Marquardt algorithm is an optimization algorithm. Optimization is to find the minimum value makes the function parameter vector.