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matlab使用BP网络的例子,使用Levenberg Marquardt算法提高训练速度,效果不错-use Matlab BP example, the use of Levenberg Marquardt algorithm to improve training speed, good results
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神经网络进行手写数字识别:
本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值.
带有图形界面-neural network handwritten numeral recognition : this program is the BP algorithm Demonstration Program, The Levenberg-Marquardt algorithm is practical value. with a graphical in
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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。
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Levenberg-Marquardt的c++优化代码。该代码适用各种非线性最小二乘问题
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Java实现的各种数学算法,如矩阵运算,
levenberg-marquardt优化算法等。
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本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值.
一、网络训练
程序默认状态是样本训练状态,现将样本训练状态下的如何训练网络进行说明:
1.系统精度:
定义系统目标精度,根据需要定义网络训练误差精度.误差公式是对训练出网络的输出层节点和实际的网络输出结果求平方差的和.
最大训练次数:
默认为10000次,根据需要调整,如果到达最大训练次数网络还未能达到目标精度,程序退出.
3.步长:
默认为0.01,由于采用
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本程序是BP算法的演示程序, 其中的Levenberg-Marquardt算法具有实用价值。随代码还提供帮助文件,非常方便。-BP algorithm Demonstration Program, which Levenberg-Marquardt algorithm has practical value. With the code also provides help files, a very convenient.
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这是一个印度人编的程序,用于两图像单应矩阵和变换结果的求取-This function estimates 2D-2D plane projective homography between two perspective images using Direct Linear Transformation, RANSAC and Levenberg Marquardt optimisation.
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LM算法的简要描述。LM算法是一种定位多变量函数最小值的迭代技术,是解决非线性最小二乘问题的基本技术之一。-The Levenberg-Marquardt(LM)algorithm is an iterative technique that locates
the minimum of a multivariate function that is expressed as the sum of squares
of non-linear real-valued functions[4
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在matlab中,最小二乘法,模型参数确定和参数检验- In matlab, least squares method, the model parameter determined
and the parameter examines
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IDL版的Marquadt优化算法,可求解非线性最小二乘问题-MPFIT uses the Levenberg-Marquardt technique to solve the
least-squares problem. In its typical use, MPFIT will be used to
fit a user-supplied function (the "model") to user-supplied data
points (the "da
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Parallel Levenberg-Marquardt-based Neural Network Training on Linux Clusters - A Case Study
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非线性优化的算法,用C++实现,比牛顿法有更快的收敛速度。-Levenberg-Marquardt nonlinear least squares algorithms in C/C++
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For training Takagi-Sugeno fuzzy systems using the Levenberg-Marquardt method
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Data assimilation (DA) is a method of combining observation data with
model forecast data in order to more accurately predict the state of a system.
One of its most common uses is in numerical weather prediction (NWP).
In NWP, we have observati
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Golden section method and Levenberg-Markardy method
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levenberg-maquardt-algorithm 是用来数学模型优化,滤波等问题的。来自美国杜克大学。-levenberg-maquardt-algorithm is used to optimize mathematical models, filtering and other issues. From Duke University.
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there is a levenber-marquardt learning algorithm for mass-spring-damper system
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Lervenberg-Marquardt 算法的实现,包括测试代码,并有辅助函数。解压缩后可直接运行,包含3个例子,在LMFnlsq2test.pdf中有对算法的详细描述。(The function is an improved version of the function LMFnlsq widely tested on the nonlinear regression, curve fitting and identification problems. Better descr ipti
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