Linear Algebra with Applications (9th Edition) by Steven J. Leon

需要的人看看就知道很有用了，英文原版，看懂不是问题！

离散控制Matlab代码LMI 最优和鲁棒控制中的线性矩阵不等式。 线性矩阵不等式：离散系统-HARISHANKAR PRABHAKARAN。 可以在本书中找到这些LMI ：。 这是一组代码，作为Wikibook中离散时间系统的示例程序（我创建的页面在下面列出，并且相应的MATLAB代码可用）： 要运行这些MATLAB代码，需要YALMIP TOOLBOX和诸如SeDuMi或IBM CPLEX之类的求解器。 A1.m-离散时间Lyapunov稳定性（Caverly 3.1.3） A2.m-离散时间有界实引理（H∞范数）（平均3.2.2） A3.m-离散时间H2规范（平均3.3.2） A4.m-离散时间稳定度（平均3.11.2） A5.m-离散时间可检测性（平均3.12.2） A6.m-离散时间H2最佳全状态反馈控制（平均4.2.2） A7.m-离散时间H2-最佳动态输出反馈控制（平均4.2.4） A8.m-离散时间H∞-最佳全状态反馈控制（平均4.3.2） A9.m-离散时间H∞-最佳动态输出反馈控制（平均4.3.4） A10.m-离散时间混合H2-H∞-最佳全状态反馈控制（平均4.4

线性优化导论，国外名师指导的讲义，深入浅出地介绍优化论的概要。

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Linear Algebra and Its Applications, Second Edition presents linear algebra as the theory and practice of linear spaces and linear maps with a unique focus on the analytical aspects as well as the numerous applications of the subject. In addition to thorough coverage of linear equations, matrices, vector spaces, game theory, and numerical analysis, the Second Edition features student-friendly additions that enhance the book's accessibility, including expanded topical coverage in the early chapters, additional exercises, and solutions to selected problems. Beginning chapters are devoted to the abstract structure of finite dimensional vector spaces, and subsequent chapters address convexity and the duality theorem as well as describe the basics of normed linear spaces and linear maps between normed spaces. Further updates and revisions have been included to reflect the most up-to-date coverage of the topic, including: The QR algorithm for finding the eigenvalues of a self-adjoint matrix The Householder algorithm for turning self-adjoint matrices into tridiagonal form The compactness of the unit ball as a criterion of finite dimensionality of a normed linear spaceAdditionally, eight new appendices have been added and cover topics such as: the Fast Fourier Transform; the spectral radius theorem; the Lorentz group; the compactness criterion for finite dimensionality; the characterization of commentators; proof of Liapunov's stability criterion; the construction of the Jordan Canonical form of matrices; and Carl Pearcy's elegant proof of Halmos' conjecture about the numerical range of matrices. Clear, concise, and superbly organized, Linear Algebra and Its Applications, Second Edition serves as an excellent text for advanced undergraduate- and graduate-level courses in linear algebra. Its comprehensive treatment of the subject also makes it an ideal reference or self-study for industry professionals.

David 的线性几何及其应用，线性代数的专业教材。

关于 一个用于将连续分段线性函数拟合到数据的库。 只需指定所需的线段数并提供数据即可。 查看！ 阅读。 现在，您可以执行分段常数拟合和分段多项式！ 特征 对于指定数量的线段，您可以确定最佳连续分段线性函数f（x）（并从中进行预测）。 请参阅。 如果知道线段终止的特定x位置，则可以拟合并预测连续的分段线性函数f（x）。 请参阅。 如果要为SciPy差分进化算法传递不同的关键字，请参见此。 您可以使用不同的优化算法，通过使用目标函数来最小化残差平方和，从而找到线段的最佳位置。 请参阅。 现在，您可以使用带有fitfast（）函数的多起点梯度优化，而不是使用差分进化。 您可以指定要使用的起点数量。 默认值为2。这意味着将使用2的拉丁超级多维数据集采样（空间填充DOE）来运行2个L-BFGS-B优化。 请参见下面的， 该示例运行fit（）函数，然后运行fitfast（）来比较运行时差

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Kalman滤波原文：《A New Approach to Linear Filtering and Prediction Problems》