David C. Lay 在美國加利福尼亞大學獲得碩士和博士學位。他是馬裏蘭大學帕剋學院數學係教授,同時還是阿姆斯特丹大學、阿姆斯特丹自由大學和德國凱澤斯勞滕大學的訪問教授。Lay教授是“綫性代數課程研究小組”的核心成員,發錶瞭30多篇關於泛函分析和綫性代數方麵的論文,並與他人閤著有多部數學教材。
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 R^n 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. Students' conceptual understanding is reinforced through True/False questions, practice problems, and the use of technology. David Lay changed the face of linear algebra with the execution of this philosophy, and continues his quest to improve the way linear algebra is taught with the new Updated Second Edition. With this update, he builds on this philosophy through increased visualization in the text, vastly enhanced technology support, and an extensive instructor support package. He has added additional figures to the text to help students visualize abstract concepts at key points in the course. A new dedicated CD and Website further enhance the course materials by providing additional support to help students gain command of difficult concepts. The CD, included in the back of the book, contains a wealth of new materials, with a registration coupon allowing access to a password-protected Website. These new materials are tied directly to the text, providing a comprehensive package for teaching and learning linear algebra.
最近想进修一下统计,遇到第一个难关就是线性代数,好多东西都忘得差不多了,只记得某年某月曾算过特征值和特征向量…… 依稀记得当年考研时候用的就是Lay老人家这本书的中文版,但想到自己已经是研究僧了,应该看看原版书了,于是决定厚颜无耻地去爱问上偷书。下...
評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...
評分看过了介绍后,感觉比较适合我。 本书是一本优秀的现代教材,给出最新的线性代数基本介绍和一些有趣应用。
評分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。
評分因为是考研学习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...
淺顯易懂,適閤像我這樣上過綫代但是需要重新撿起來的人閱讀,裏麵給的應用也比較切閤實際,Numerical Note還可以在算法上提供一些建議。比國內的教材好的不是一星半點
评分綫代基礎
评分不多的完整讀完的幾本數學書,在第一章就講到瞭綫性變換,附以圖形和解釋,也不會讓人覺得太唐突,確實厲害。老外的書以書中圖形多少作為書的一個亮點,國人為什麼做不到呢?
评分綫代基礎
评分大愛~~~~寫的相當相當好!
本站所有內容均為互聯網搜索引擎提供的公開搜索信息,本站不存儲任何數據與內容,任何內容與數據均與本站無關,如有需要請聯繫相關搜索引擎包括但不限於百度,google,bing,sogou 等
© 2025 qciss.net All Rights Reserved. 小哈圖書下載中心 版权所有