Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares

一本从事信息论和通信理论与技术研究的好书,适合工程开发和理论研究使用

该软件包包含 8 种不同的 K 均值聚类技术，适用于一组对称正定 (SPD) 矩阵。 基于 (1) 用于将样本与聚类中心进行比较的距离/散度度量，以及 (2) 相应的平均计算技术，即增量与非增量，算法是不同的。 这里使用的相异度量是：(1) P(n) 上的自然测地距离，(2) Stein 距离，(3) LogEuclidean 距离和 (4) Kullback-Leibler 散度。 基于上述不同度量，在增量和非增量框架中都提供了均值计算方法。 如果您使用该软件，请引用以下论文： [1] 广程、Hesamoddin Salehian、Baba C. Vemuri，计算平均扩散张量的高效递归算法及其在 DTI 分割中的应用，欧洲计算机视觉会议 (ECCV) 2012。 [2] Jeffrey Ho、Guang Cheng、Hesamoddin Salehian、Baba C. Vem

一本学习image deblurring的很好的入门教材，DjVu格式的； Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms) By Per Christian Hansen Publisher: Society for Industrial and Applied Mathematic Number Of Pages: 130 Publication Date: 2006-10-29 ISBN-10 / ASIN: 0898716187 ISBN-13 / EAN: 9780898716184

【作 者】Per Christian Hansen 【出版社】Society for Industrial and Applied Mathematic 【出版日期】October 29, 2006 【ISBN】0898716187 9780898716184 【形态项】9.8 x 6.7 x 0.3 inches 【语 言】English 【价 格】$63.00 Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms) By Per Christian Hansen Publisher: Society for Industrial and Applied Mathematic Number Of Pages: 130 Publication Date: 2006-10-29 ISBN-10 / ASIN: 0898716187 ISBN-13 / EAN: 9780898716184 Binding: Paperback “The book’s focus on imaging problems is very unique among the competing books on inverse and ill-posed problems. …It gives a nice introduction into the MATLAB world of images and deblurring problems.” — Martin Hanke, Professor, Institut für Mathematik, Johannes-Gutenberg-Universität. When we use a camera, we want the recorded image to be a faithful representation of the scene that we see, but every image is more or less blurry. In image deblurring, the goal is to recover the original, sharp image by using a mathematical model of the blurring process. The key issue is that some information on the lost details is indeed present in the blurred image, but this “hidden” information can be recovered only if we know the details of the blurring process. Deblurring Images: Matrices, Spectra, and Filtering describes the deblurring algorithms and techniques collectively known as spectral filtering methods, in which the singular value decomposition—or a similar decomposition with spectral properties—is used to introduce the necessary regularization or filtering in the reconstructed image. The concise MATLAB® implementations described in the book provide a template of techniques that can be used to restore blurred images from many applications. This book’s treatment of image deblurring is unique in two ways: it includes algorithmic and implementation details; and by keeping the formulations in terms of matrices, vectors, and matrix computations, it makes the material access

This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics covered include: the choice of cost function and robustness; numerical optimization including sparse Newton methods, linearly convergent approximations, updating and recursive methods; gauge (datum) invariance; and quality control. The theory is developed for general robust cost functions rather than restricting attention to traditional nonlinear least squares.

矩阵函数计算的教材，英国皇家学会会员、曼彻斯特大学教授N. Higham所著。

This book gives a coherent and detailed description of analytical methods devised to study random matrices. These methods are critical to the understanding of various fields in in mathematics and mathematical physics, such as nuclear excitations, ultrasonic resonances of structural materials, chaotic systems, the zeros of the Riemann and other zeta functions. More generally they apply to the characteristic energies of any sufficiently complicated system and which have found, since the publication of the second edition, many new applications in active research areas such as quantum gravity, traffic and communications networks or stock movement in the financial markets. This revised and enlarged third edition reflects the latest developements in the field and convey a greater experience with results previously formulated. For example, the theory of skew-orthogoanl and bi-orthogonal polynomials, parallel to that of the widely known and used orthogonal polynomials, is explained here for the first time.

Direct Methods for Sparse Matrices (I. S. Duff, A. M. Erisman, J. K. Reid).pdf

第二版矩阵了理论分析，很好的资源，大家快来下载吧！