Nonlinear equation system solver_ broyden.zip，这是一份不错的文件

Since the 4e appeared, a fast evolution of the field has occurred. The 5e of this classic work provides an up-to-date account of the nonlinear phenomena occurring inside optical fibers, the basis of all our telecommunications infastructure as well as being used in the medical field. Reflecting the big developments in research, this new edition includes major new content: slow light effects, which offers a reduction in noise and power consumption and more ordered network traffic-stimulated Brillouin scattering; vectorial treatment of highly nonlinear fibers; and a brand new chapter on supercontinuum generation in optical fibers.

这是关于非线性有限元方法的电子书，高清，最新版本，经典著作，英文版

小参 该存储库包含由GraphOptimization（Beijing），Inc.开发的轻量级图形优化库的代码。 感谢gtsam的作者。 我们仅将核心功能和类保留在gtsam中。 编写库时，请遵循以下规则。 尽可能少使用模板。 没有使用boost库。 没有特质。 没有智能指针。 自给自足。 要求： gcc编译器版本：5.4.0 20160609（Ubuntu 5.4.0-6ubuntu1〜16.04.11） 高于2.6版的CMake 安装： 将项目克隆到本地。 git clone 运行命令： cd minisam_lib mkdir build cd build cmake .. sudo make install 平台： 仅支持Ubuntu。 对于其他平台，您可以与我们联系。 接触： 如果您有任何需求，请在github上提出问题，或发送电子邮

Lecture book of Daniel Liberzon

非线性系统 Hassan_k_khalil

非线性有限元分析经典教材 Wiley 2000 全英文版

经典教材，讲述线性和非线性方面的优化问题。

This book is intended as a text covering the central concepts of practical optimization techniques. It is designed for either self-study by professionals or classroom work at the undergraduate or graduate level for students who have a technical background in engineering, mathematics, or science. Like the field of optimization itself, which involves many classical disciplines, the book should be useful to system analysts, operations researchers, numerical analysts, management scientists, and other specialists from the host of disciplines from which practical optimization applications are drawn. The prerequisites for convenient use of the book are relatively modest; the prime requirement being some familiarity with introductory elements of linear algebra. Certain sections and developments do assume some knowledge of more advanced concepts of linear algebra, such as eigenvector analysis, or some background in sets of real numbers, but the text is structured so that the mainstream of the development can be faithfully pursued without reliance on this more advanced background material.

稳健的回归和离群值检测 使用贝叶斯迭代将已知模型稳固地拟合到数据。 这两个实现使用 兰萨克 M估计 健壮的部分实现了，而功能却没有实现。 模型拟合是从scipy.minimize借用的。 随意使用其他模型拟合方法。 要求 numpy是robust_lsq.py的唯一先决条件。 robust_lsq.py需要最小二乘拟合函数（或其他拟合函数），例如scipy.optimize.minimize 。 请参阅示例models.py 。 robust_lsq.py 麻木 models.py 科学的 麻木 test.py 科学的 麻木 matplotlib 设置 请运行test.py以获取使用贝叶斯估计将直线稳固地拟合到数据的示例。 它是如何工作的？ 关键思想是确定最适合模型的样本。 使用贝叶斯更新。 贝叶斯规则由下式给出： P（数据/模型）= P（模型/数据）* P（数据）/ p（模型）