James Stewart微积分,国外优秀教材
2022-07-22 14:03:20 67.54MB 微积分
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This book is designed to introduce the reader to the theory of semisimple Lie algebras over an algebraically closed field of characteristic 0, with emphasis on representations. A good knowledge of linear algebra (including eigenvalues, bilinear forms, euclidean spaces, and tensor products of vector spaces) is presupposed, as well as some acquaintance with the methods of abstract algebra. The first four chapters might well be read by a bright undergraduate; however, the remaining three chapters are admittedly a little more demanding. Besides being useful in many parts of mathematics and physics, the theory of semisimple Lie algebras is inherently attractive, combining as it does a certain amount of depth and a satisfying degree of completeness in its basic results. Since Jacobson's book appeared a decade ago, improvements have been made even in the classical parts of the theory. I have tried to incor- porate some of them here and to provide easier access to the subject for non-specialists. For the specialist, the following features should be noted: (1) The Jordan-Chevalley decomposition of linear transformations is emphasized, with "toral" subalgebras replacing the more traditional Cartan subalgebras in the semisimple case. (2) The conjugacy theorem for cartan subalgebras is proved (following D. J. Winter and G. D. Mostow) by elementary Lie algebra methods, avoiding the use of algebraic geometry. (3) The isomorphism theorem is proved first in an elementary way (Theorem 14.2), but later obtained again as a corollary of Serre's Theorem (18.3), which gives a presentation by generators and relations. (4) From the outset, the simple algebras of types A, B, C, D are empha- sized in the text and exercises. (5) Root systems are treated axiomatically (Chapter III), along with some of the theory of weights. (6) A conceptual approach to Weyl's character formula, based on Harish-chandra's theory of "characters" and independent of Freudenthal's multiplicity formula (22.3), is presented in 23 and 24. This is inspired by D.-N. Verma's thesis, and recent work of I. N. Bernstein, I. M. Gel'fand, S. I. Gel'fand. (7) The basic constructions in the theory of Chevalley groups are given in Chapter VII, following lecture notes of R. Steinberg. I have had to omit many standard topics (most of which I feel are better suited to a second course), e.g., cohomology, theorems of Levi and Mal'cev, theorems of Ado and Iwasawa, classification over non-algebraically closed fields, Lie algebras in prime characteristic. I hope the reader will be stirn u- lated to pursue these topics in the books and articles listed under References, especially Jacobson [1], Bourbaki [1], [2], Winter [1], Seligman [1].
2022-07-08 11:00:01 2.84MB Lie Algebras Representation Theory
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james使用(一):windows环境下james3.0.1版本邮件服务器搭建及配置-附件资源
2022-06-15 14:00:00 23B
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Natural Language Understanding 自然语言理解 第2版 James Allen
2022-06-06 14:37:46 5.12MB Natural Language Understanding 自然语言理解
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拓扑学 (原书第2版) (美)James R. Munkres著;熊金城, ((美)JAMES R.MUNKRES著
2022-05-30 10:04:56 20.4MB 拓扑学 r语言 开发语言
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2022-04-19 13:07:22 635KB JAMES电玩离线工具
James Munkres Topology
2022-02-13 17:45:21 9.73MB Math
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占士邦 公司债券评级变化预测模型 团队成员:Wes Sapone,Kwame van Leeuwen,Ketan Patel,Susan Fan 目标:开发一种机器学习模型,该模型可以预测未来12个月公司债券的信用等级变化 概括 通过SQL从活跃于公司信用违约概率建模的公司中获取大型数据集。 数据清理在该项目中发挥了重要作用。 3个分类模型:使用Logistic回归,随机森林和梯度提升来训练/测试模型并分析大型历史数据框。 事实证明,拥有相对较少的评分事件的不平衡数据集是一个关键挑战。 使用原始的不平衡数据集,Random Forest和Gradient Boost模型似乎优于Logistic回归模型,其平衡精度得分约为83%。 将来可能进行的建模改进包括增强数据集,微调模型和优化目标变量。 演示幻灯片 数据清理 楷模 逻辑回归 随机森林 原始数据,默认参数1 随机森林原始数据,
2022-01-16 14:01:40 15.49MB JupyterNotebook
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有关代码方法的详细信息,请参阅相应的论文“ Yue Wu,Brian Tracey,Premkumar Natarajan,Joseph P. Noonan:用于非本地均值图像降噪的James-Stein类型中心像素权重。 20(4): 411-414 (2013)" http://dx.doi.org/10.1109/LSP.2013.2247755
2022-01-11 13:34:55 3KB matlab
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James R. Munkres - Topology.djvu 拓扑方面很好的一本书
2021-12-25 19:36:48 3.96MB James R. Munkres -
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