English translation for "levenberg-marquardt method"
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- 列文伯格
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| 1. | Levenberg - marquardt method is one of the most important methods for solving systems of nonlinear equations
Levenberg - marquardt方法是求解非线性方程组的最重要的方法之一。 | | 2. | Fan and yuan [ 6 ] uses another method that has proved under the local error bound condition , if we choice the parameter as the norm of the function , the sequence produced by the levenberg - marquardt method converges quadraticlly to a solution of the system of the equations
如此选取参数有一些不足之处。范、袁在[ 6 ]中用另一种方法证明了当迭代参数为当前迭代点处函数值的模时， levenberg - marquardt方法具有二阶收敛性。 | | 3. | Detailed procedure of the algorithm is proposed in this paper , using levenberg - marquardt method combined with gauss - newton strategy . and the corresponding software named limap ( inverse identification of material parameters ) is self - developed for solving such a nonlinear least square problem
本文采用levenberg - marquardt方法，同时混合了gauss - newton法的策略，详细推导出了材料参数反求的算法，在自行研制的参数反求软件iimap中实现了材料参数反求这样一个非线性最小二乘问题的求解。 | | 4. | Recently , yamashita and fukushima [ 4 ] show that the sequence produced by the levenberg - marquardt method converges quadraticlly to the solution set of the equations , if the parameter is chosen as the quadratic norm of the function and under the weaker condition than the nonsingularity that the function provides a local error bound near the solution . however , the quadratic term has some unsatisfactory properties
最近yamashita & fukushima [ 4 ]提出，在弱于非奇异性条件的局部误差界条件下，如果选取的迭代参数为当前迭代点处函数值模的平方，则levenberg - marquardt方法产生的迭代点列二阶收敛于方程组的解集。 | | 5. | In the simulation of functions , this method performs better than chaotic optimization algorithm . with the combination of bisection - interpolation approach and gauss newton levenberg - marquardt method , we optimize neural network and fuzzy inference system . taking advantage of bisection - interpolation approach , simulated annealing algorithm and genetic algorithm find the better solution than chaotic combination method
作者通过大量的函数仿真以及将其与牛顿高斯levenberg一manquardt方法、模拟退火、遗传算法等常用算法相结合，形成的混合优化算法，对神经网络、模糊神经网络和函数进行了优化，其优化效果明显优于混饨以及混饨混合优化算法。 | | 6. | In the application of mini - micro - robot visual perception , there is a need for fish - eye lenses for capturing wide field of view for navigation . though fish - eye lenses provide a wide field of view ( 180 ) , they introduce significant distortion in images and the acquired images are quite warped , which makes conventional camera calibration algorithms no longer work well . this paper presents an accurate calibration framework for fish - eye lens ( a high distortion lens ) camera stereo vision system . the accurate calibration model is formulated with radial distortion , decentering distortion and thin prism distortion based on the fisheye deformation model . using fish - eye and non - linear camera model , the author employs levenberg - marquardt method to realize precise non - linear calibration for wide - view - scene dense depth image recovery
鱼眼镜头成像立体视觉系统在微小型机器人视觉导航和近距离大视场物体识别与定位中有着广泛的应用.尽管鱼眼镜头摄像机具有很大的视场角(接近180 ) ，但同时也引入严重的图像变形，常规的摄像机标定方法无法使用.该文提出一种标定鱼眼镜头摄像机立体视觉系统的方法.在鱼眼镜头变形模型的基础上，通过考虑鱼眼镜头成像的径向变形、偏心变形和薄棱镜变形，建立了鱼眼镜头成像的精确成像模型,然后，利用非线性迭代算法，精确求解摄像机外部参数、内部参数.实验表明，使用该方法得到的立体视觉系统参数满足精确恢复大场景稠密深度图的要求 | | 7. | The aim of projective reconstructing is to estimate the position and direction of cameras through matching points in different images so lay the foundation for further reconstructing . on the basis of current methods of projective reconstructing , we used the levenberg - marquardt method to optimize the result of linear method so the precision is be improved , and we use the bundle adjustment method to entirely optimize the structure of scene and projective matrixes
本文在研究已有射影重建算法的基础上，利用l - m算法对基于基础矩阵的射影重建算法得到的线性结果进行优化，提高了算法的估计精度和稳定性，并在求得所有图象对应的投影矩阵后利用bundleadjustment方法对空间结构及投影矩阵进行全局优化。 | | 8. | Here we consider the choice of the parameter as the norm of the gratitude of the function . we prove under the local error bound condition that the levenberg - marquardt method with this parameter converges quadraticlly to a solution of the system of the equations . and we also present two globally convergent levenberg - marquardt algorithms using line search techniques and trust region approach respectively
我们提出选取迭代参数为当前迭代点处函数梯度的模，在局部误差界条件下， levenberg - marquardt方法依然具有二阶收敛性，并考虑了线搜索和信赖域技巧的levenberg - marquardt方法，分析了其全局收敛性。 |
- Similar Words：
- "leven" English translation, "leven bk" English translation, "leven loch" English translation, "levenard" English translation, "levenberg" English translation, "levenbraum" English translation, "levend" English translation, "levenda" English translation, "levenday" English translation, "levendel" English translation
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