David C. Lay 在美国加利福尼亚大学获得硕士和博士学位。他是马里兰大学帕克学院数学系教授,同时还是阿姆斯特丹大学、阿姆斯特丹自由大学和德国凯泽斯劳滕大学的访问教授。Lay教授是“线性代数课程研究小组”的核心成员,发表了30多篇关于泛函分析和线性代数方面的论文,并与他人合著有多部数学教材。
Linear algebra is relatively easy for students during the early stages of the course, when the material is presented in a familiar, concrete setting. But when abstract concepts are introduced, students often hit a brick wall. Instructors seem to agree that certain concepts (such as linear independence, spanning, subspace, vector space, and linear transformations), are not easily understood, and require time to assimilate. Since they are fundamental to the study of linear algebra, students' understanding of these concepts is vital to their mastery of the subject. Lay introduces these concepts early in a familiar, concrete Rn setting, develops them gradually, and returns to them again and again throughout the text. Finally, when discussed in the abstract, these concepts are more accessible. It includes easily identifiable Matlab icons in the margins next to Matlab examples and exercises and a CD-Rom bound in the back of the book includes additional Matlab exercises and programs. Instructor's Edition now includes selected solutions and MyMathLab. In this book fundamental ideas of linear algebra are introduced within the first seven lectures, in the concrete setting of Rn, and then gradually examined from different points of view. Later generalizations of these concepts appear as natural extensions of familiar ideas. The focus is on visualization of concepts throughout the book and it has icons in the margins to flag topics for which expanded or enhanced material is available on the Web; a modern view of matrix multiplication is presented. Definitions and proofs focus on the columns of a matrix rather than on the matrix entries; Numerical Notes give a realistic flavor to the text. Students are reminded frequently of issues that arise in the real-life use of linear algebra; and each major concept in the course is given a geometric interpretation because many students learn better when they can visualize an idea.
因为是考研学习LA 所以看了全国被普遍采用的那本紫色的同济LA教材,看着看着我发现那本书其实只是一本 线性代数公式大全,言简意赅到一个境界了,不适合我这样的普通智商的学生参读。 后来选择了这本LA&applications 觉得很不错。每章用一个introductory example开头 让人...
评分昨天在图书馆翻了翻"时间序列分析"的书,发现这东西还是很有用的,利用时间作为自变量来预测一个时间序列未来的值,比如,可以预测地震、天气、股票等等,由于它的自变量只有时间,所以感觉很神奇,几乎就是拿一个变量自己来做回归,称之为自回归AR(auto regression),另...
评分PCA这么重要的东西应该与SVD一样专门写一段,而不是放在“7.5 图像处理和统计学中的应用”底下当成普通例子来写。虽然这里PCA写的是真清晰真透彻,秒杀网上无数介绍。另外,SVD讲的太简略了,看完公式也抓不住本质。最好加入几何理解角度,并谈谈与PCA的异同。
评分在学习的同时,知道很多应用实例,记忆非常深刻。 学完这本书,对线性代数的应用可以到一定的广度的了解 但是学完国内一般的线性代数教材,觉得还是非常虚幻。强烈建议国内大学实用。
评分A first course in linear algebra is dramatically different from most mathematics courses that precede it.The focus shifts from learning computational procedures to digesting and mastering basic concepts that underlie the computations.To survive,you may need...
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