An Interactive Introduction to Mathematical Analysis Hardback with CD-ROM
An Interactive Introduction to Mathematical Analysis Hardback with CD-ROM

Author: Jonathan Lewin

Publisher: Cambridge University Press

Published: 2003-01-13

Total Pages: 532

ISBN-13: 9780521815895

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This book provides a rigorous course in the calculus of functions of a real variable. Its gentle approach, particularly in its early chapters, makes it especially suitable for students who are not headed for graduate school but, for those who are, this book also provides the opportunity to engage in a penetrating study of real analysis.The companion onscreen version of this text contains hundreds of links to alternative approaches, more complete explanations and solutions to exercises; links that make it more friendly than any printed book could be. In addition, there are links to a wealth of optional material that an instructor can select for a more advanced course, and that students can use as a reference long after their first course has ended. The on-screen version also provides exercises that can be worked interactively with the help of the computer algebra systems that are bundled with Scientific Notebook.

An Interactive Introduction to Mathematical Analysis Paperback with CD-ROM
An Interactive Introduction to Mathematical Analysis Paperback with CD-ROM

Author: Jonathan Lewin

Publisher: Cambridge University Press

Published: 2003-01-13

Total Pages: 530

ISBN-13: 9780521017183

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This book provides a rigorous course in the calculus of functions of a real variable. Its gentle approach, particularly in its early chapters, makes it especially suitable for students who are not headed for graduate school but, for those who are, this book also provides the opportunity to engage in a penetrating study of real analysis.The companion onscreen version of this text contains hundreds of links to alternative approaches, more complete explanations and solutions to exercises; links that make it more friendly than any printed book could be. In addition, there are links to a wealth of optional material that an instructor can select for a more advanced course, and that students can use as a reference long after their first course has ended. The on-screen version also provides exercises that can be worked interactively with the help of the computer algebra systems that are bundled with Scientific Notebook.

Interactive Linear Algebra with Maple V
Interactive Linear Algebra with Maple V

Author: Elias Deeba

Publisher: Springer Science & Business Media

Published: 1998-03-16

Total Pages: 338

ISBN-13: 9780387982403

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A complete software package consisting of the printed book and a CD-ROM (with diskettes available on request). The interactive text includes: * A graphical user interface for easy navigation through the text along with animations that explain linear algebra concepts geometrically. * Interactive lessons with emphasis on experimentation and conjecturing. * A collection of labs which strengthens the learning of the concepts. * Applications which stress modelling and the use of linear algebra in various disciplines. * A unique library of interactive "high-level" functions written in Maple V that can be used in different modes. * A stand alone testing system. The authors believe that students of mathematics should enjoy, understand, assimilate, and apply the skills and concepts they study, and, as such, here they play a fundamental and active role throughout the learning process.

Foundations of Mathematical Analysis
Foundations of Mathematical Analysis

Author: Richard Johnsonbaugh

Publisher: Courier Corporation

Published: 2012-09-11

Total Pages: 450

ISBN-13: 0486134776

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Definitive look at modern analysis, with views of applications to statistics, numerical analysis, Fourier series, differential equations, mathematical analysis, and functional analysis. More than 750 exercises; some hints and solutions. 1981 edition.

Introduction to Probability Models
Introduction to Probability Models

Author: Wayne L. Winston

Publisher: Duxbury Resource Center

Published: 2004

Total Pages: 762

ISBN-13:

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Vol. 2: CD-ROM contains student editions of: ProcessModel, LINGO, Premium Solver, DecisionTools Suite including @RISK AND RISKOptimizer, Data files.

Feedback Systems
Feedback Systems

Author: Karl Johan Åström

Publisher: Princeton University Press

Published: 2021-02-02

Total Pages:

ISBN-13: 069121347X

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The essential introduction to the principles and applications of feedback systems—now fully revised and expanded This textbook covers the mathematics needed to model, analyze, and design feedback systems. Now more user-friendly than ever, this revised and expanded edition of Feedback Systems is a one-volume resource for students and researchers in mathematics and engineering. It has applications across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl Åström and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Åström and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. Features a new chapter on design principles and tools, illustrating the types of problems that can be solved using feedback Includes a new chapter on fundamental limits and new material on the Routh-Hurwitz criterion and root locus plots Provides exercises at the end of every chapter Comes with an electronic solutions manual An ideal textbook for undergraduate and graduate students Indispensable for researchers seeking a self-contained resource on control theory

Mathematics for Machine Learning
Mathematics for Machine Learning

Author: Marc Peter Deisenroth

Publisher: Cambridge University Press

Published: 2020-04-23

Total Pages: 392

ISBN-13: 1108569323

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The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Measure, Integration & Real Analysis
Measure, Integration & Real Analysis

Author: Sheldon Axler

Publisher: Springer Nature

Published: 2019-11-29

Total Pages: 430

ISBN-13: 3030331431

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This open access textbook welcomes students into the fundamental theory of measure, integration, and real analysis. Focusing on an accessible approach, Axler lays the foundations for further study by promoting a deep understanding of key results. Content is carefully curated to suit a single course, or two-semester sequence of courses, creating a versatile entry point for graduate studies in all areas of pure and applied mathematics. Motivated by a brief review of Riemann integration and its deficiencies, the text begins by immersing students in the concepts of measure and integration. Lebesgue measure and abstract measures are developed together, with each providing key insight into the main ideas of the other approach. Lebesgue integration links into results such as the Lebesgue Differentiation Theorem. The development of products of abstract measures leads to Lebesgue measure on Rn. Chapters on Banach spaces, Lp spaces, and Hilbert spaces showcase major results such as the Hahn–Banach Theorem, Hölder’s Inequality, and the Riesz Representation Theorem. An in-depth study of linear maps on Hilbert spaces culminates in the Spectral Theorem and Singular Value Decomposition for compact operators, with an optional interlude in real and complex measures. Building on the Hilbert space material, a chapter on Fourier analysis provides an invaluable introduction to Fourier series and the Fourier transform. The final chapter offers a taste of probability. Extensively class tested at multiple universities and written by an award-winning mathematical expositor, Measure, Integration & Real Analysis is an ideal resource for students at the start of their journey into graduate mathematics. A prerequisite of elementary undergraduate real analysis is assumed; students and instructors looking to reinforce these ideas will appreciate the electronic Supplement for Measure, Integration & Real Analysis that is freely available online. For errata and updates, visit https://measure.axler.net/