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Levenberg-Marquardt
- 这里有个Levenberg-Marquardt算法的程序和ppt介绍-Here' s a Levenberg-Marquardt algorithm described procedures and ppt
znzx
- 阻尼最小二乘法（即Levenberg-Marquarat算法)，是Gauss-Newton算法的一种修正法。-Damped least squares method (that is, Levenberg-Marquarat algorithm), Gauss-Newton algorithm are an Amendment Act.
Delineation
- This routine performs automatic curve fitting of overlapping lines. It uses a Levenberg-Marquardt fitting routine. The fit function can be Lorentzian, Gaussian or Mixed Lorentzian and Gaussian. Use Options->Line Fit to activate the line fitting pr
Levenberg-Marquardt
- 基于Levenberg-Marquardt算法和最小二乘方法的小波网络混合学习算法-Levenberg-Marquardt algorithm based on least squares method and hybrid learning algorithm of wavelet network
Levenberg-Marquardt
- L-M算法的简单介绍及部分matlab程序-Brief LM algorithm and some matlab procedures
LMFnlsq2
- Levenberg–Marquardt 算法实现非线性拟合-Levenberg–Marquardt non-linear fitting algorithm
LMFnlsq2testPDF
- L-M(Levenberg—Marquardt)是一种非线性最优化里面最常用的方法之一，改方法能快速而准确的逼近收敛值。本文简述了改方法的操作原理和具体运用，如可以方便的用于有约束与无约束最优化的求解。-L- M (Levenberg- Marquardt) is a kind of nonlinear optimization inside one of the most commonly used method, change method can fast and accurate app
Levenberg-Marquardt-Algorithm
- 求解非线性问题的一种算法，综合了梯度法和牛顿法的优点-An algorithm for solving nonlinear problem, taking advantages of gradient method and Newton method
Levenberg-Marquardt-Method
- Levenberg–Marquardt Method，LM拟合优化算法的Matlab平台.m文件的实现-Levenberg–Marquardt Method. The inplementation of matlab.m
Extract_VTO_GAMMA_PHI
- Extraction VTO. GAMMA, PHI for EKV MOSFET Model using Levenberg–Marquardt algorithm.
hw5_LM_handout2
- This a brief tutorial on refining the Camera Calibration parameters using the Levenberg Marquardt (LM) algorithm in C++. For readers who are new to LM and camera calibration, links to useful sites and documents are provided below-This is a brief
Novel-Neuronal-Activation
- Feedforward neural network structures have extensively been considered in the literature. In a significant volume of research and development studies hyperbolic tangent type of a neuronal nonlinearity has been utilized. This paper dwells on the w