Basic Analysis, (5 Volumes Set)

Title: Basic Analysis, (5 Volumes Set)
Author: James K. Peterson
ISBN: 113805514X / 9781138055148
Format: Hard Cover
Pages: 2688
Publisher: CHAPMAN & HALL
Year: 2021
Availability: In Stock

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Basic Analysis: Volumes I–V is written with the aim of balancing theory and abstraction with clear explanations and arguments, so that students and researchers alike who are from a variety of different areas can follow this text and use it profitably for self-study.

The first volume is designed for students who have completed the usual calculus and ordinary differential equation sequence and a basic course in linear algebra. This is a critical course in the use of abstraction, but is just first volume in a sequence of courses which prepare students to become practicing scientists.

The second volume focuses on differentiation in n-dimensions and important concepts about mappings between finite dimensional Euclidean spaces, such as the inverse and implicit function theorem and change of variable formulae for multidimensional integration. These important topics provide background in important applied and theoretical areas which are no longer covered in mathematical science curricula. Although it follows on from the preceding volume, this is a self-contained book, accessible to undergraduates with a standard course in undergraduate analysis.

The third volume is intended as a first course in abstract linear analysis. This textbook covers metric spaces, normed linear spaces and inner product spaces, along with many other deeper abstract ideas such a completeness, operators and dual spaces. These topics act as an important tool in the development of a mathematically trained scientist.

The fourth volume introduces students to concepts from measure theory and continues their training in the abstract way of looking at the world. This is a most important skill to have when your life's work will involve quantitative modeling to gain insight into the real world. This text generalizes the notion of integration to a very abstract setting in a variety of ways. We generalize the notion of the length of an interval to the measure of a set and learn how to construct the usual ideas from integration using measures. We discuss carefully the many notions of convergence that measure theory provides.

The final volume introduces graduate students in science with concepts from topology and functional analysis, both linear and nonlinear. It is the fifth book in a series designed to train interested readers how to think properly using mathematical abstractions, and how to use the tools of mathematical analysis in applications.

It is important to realize that the most difficult part of applying mathematical reasoning to a new problem domain is choosing the underlying mathematical framework to use on the problem. Once that choice is made, we have many tools we can use to solve the problem. However, a different choice would open up avenues of analysis from a different, perhaps more productive perspective. In this volume, the nature of these critical choices is discussed using applications involving the immune system and cognition.

Features:

  • Can be used as a supplementary text for anyone whose work requires that they begin to assimilate more abstract mathematical concepts as part of their professional growth
  • Function as a traditional textbook as well as a resource for self-study
  • Suitable for mathematics students and for those in other disciplines such as biology, physics, and economics and others requiring a careful and solid grounding in the use of abstraction in problem solving
  • Emphasizes learning how to understand the consequences of the underlying assumptions used in building a model
  • Regularly uses computation tools to help understand abstract concepts.

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Basic Analysis I : Functions of a Real Variable

Part I : Introduction
Chapter 1 : Introduction

Part II : Understanding Smoothness
Chapter 2 : Proving Propositions
Chapter 3 : Sequences of Real Numbers
Chapter 4 : Bolzano - Weierstrass Results
Chapter 5 :  Topological Compactness
Chapter 6 : Function Limits
Chapter 7 : Continuity
Chapter 8 : Consequences of continuity of intervals
Chapter 9 : Lower Semicontinuous and Convex Functions
Chapter 10 : Basic Differentiability
Chapter 11 : The Properties of Derivatives
Chapter 12 : Consequences of Derivatives
Chapter 13 : Exponential and Logarithm Functions
Chapter 14 : Extremal Theory for One Variable
Chapter 15 : Differentiation in R2 and R3
Chapter 16 : Multivariable Extremal Theory

Part III : Integration and Sequences of Functions
Chapter 17 : Uniform Continuity
Chapter 18 : Cauchy Sequences of Real Numbers
Chapter 19 :  Series of Real Numbers
Chapter 20 : Series in General
Chapter 21 :  Integration Theory
Chapter 22 : Existence of Reimann Integral and Properties
Chapter 23 : The Fundamental Theorem of Calculus (FTOC)
Chapter 24 :  Convergence of sequences of functions
Chapter 25 :  Series of Functions and Power Series
Chapter 26 : Riemann Integration  : Discontinuities and Compositions
Chapter 27 : Fourier Series
Chapter 28 : Applications

Part IV : Summing it All Up 
Chapter 29 : Summary

Part V :  References
Part VI :  Detailed Index

Basic Analysis II : A Modern Calculus in Many Variables

Part I : Introduction
Chapter 1 : Beginning Remarks 

Part II : Linear Mappings
Chapter 2 : Preliminaries 
Chapter 3 : Vector Spaces 
Chapter 4 : Linear Transformations 
Chapter 5 : Symmetric Matrices 
Chapter 6 : Continuity and Topology 
Chapter 7 : Abstract Symmetric Matrices 
Chapter 8 : Rotations and Orbital Mechanics 
Chapter 9 : Determinants and Matrix Manipulations 

Part III : Calculus of Many Variables
Chapter 10 : Differentiability 
Chapter 11 : Multivariable Extremal Theory 
Chapter 12 : The Inverse and Implicit Function Theorems 
Chapter 13 : Linear Approximation Applications 

Part IV : Integration
Chapter 14 : Integration in Multiple Dimensions 
Chapter 15 : Change of Variables and Fubini’s Theorem 
Chapter 16 : Line Integrals 
Chapter 17 : Differential Forms 

Part V : Applications
Chapter 18 : The Exponential Matrix 
Chapter 19 : Nonlinear Parametric Optimization Theory 

Part VI : Summing It All Up
Chapter 20 : Summing It All Up

Part VII : References
Part VIII : Detailed Index 

Basic Analysis III : Mappings on Infinite Dimensional Spaces

Part I : Introduction 
Chapter 1 : Introduction

Part II : Metric Spaces
Chapter 2 : Metric Spaces
Chapter 3 : Completing a Metric Space

Part III : Normed Linear Spaces
Chapter 4 : Vector Spaces
Chapter 5 : Normed Linear Spaces
Chapter 6 : Linear Operators on Normed Spaces

Part IV : Inner Product Spaces
Chapter 7 : Inner Product Spaces
Chapter 8 : Hilbert Spaces
Chapter 9 : Dual Spaces
Chapter 10 : Hahn - Banach Results
Chapter 11 : More About Dual Spaces
Chapter 12 : Some Classical Results

Part V : Operators
Chapter 13 : Sturm–Liouville Operators
Chapter 14 : Self Adjoint Operators

Part VI : Topics in Applied Modeling
Chapter 15 : Fields and Charges on a Set
Chapter 16 : Games

Part VII : Summing It All Up
Chapter 17 : Summing It All Up

Part VIII : References
Part IX : Detailed Index

Basic Analysis IV : Measure Theory and Integration

Part I : Introductory Matter
Chapter 1 : Introduction

Part II : Classical Riemann Integration
Chapter 2 : An Overview of Riemann Integration
Chapter 3 : Bounded Variation
Chapter 4 : Riemann Integration
Chapter 5 : Further Riemann Results

Part III : Riemann - Stieltjes Integration
Chapter 6 : The Riemann-Stieltjes Integral
Chapter 7 : Further Riemann - Stieljes Results

Part IV : Abstract Measure Theory One
Chapter 8 : Measurability
Chapter 9 : Abstract Integration
Chapter 10 : The Lp Spaces

Part V : Constructing Measures
Chapter 11 : Building Measures
Chapter 12 : Lebesgue Measure
Chapter 13 : Cantor Sets
Chapter 14 : Lebesgue Stieljes Measure

Part VI : Abstract Measure Theory Two
Chapter 15 : Convergence Modes
Chapter 16 : Decomposing Measures
Chapter 17 : Connections to Riemann Integration
Chapter 18 : Fubini Type Results
Chapter 19 : Differentiation

Part VII : Summing It All Up
Chapter 20 : Summing It All Up

Part VIII : References
Part IX : Index

Part X : Appendix : Undergraduate Analysis Background Check
Appendix A : Undergraduate Analysis Part One
Appendix B : Undergraduate Analysis Part Two

Part XI : Appendix : Linear Analysis Background Check
Appendix C : Linear Analysis

Part XII : Appendix : Preliminary Examination Check
Appendix D : The Preliminary Examination in Analysis

Basic Analysis V : Functional Analysis and Topology

Part I : Introduction
Chapter 1 : Introduction

Part II : Some Algebraic Topology
Chapter 2 : Basic Metric Space Topology
Chapter 3 : Forms and Curves
Chapter 4 : The Jordan Curve Theorem

Part III : Deeper Topological Ideas
Chapter 5 : Vector Spaces and Topology
Chapter 6 : Locally Convex Spaces and Seminorms
Chapter 7 : A New Look at Linear Functionals
Chapter 8 : Deeper Results on Linear Functionals
Chapter 9 : Stone - Weierstrass Results

Part IV : Topological Degree Theory
Chapter 10 : Brouwer Degree Theory
Chapter 11 : Leray - Schauder Degree
Chapter 12 : Coincidence Degree

Part V : Manifolds
Chapter 13 : Manifolds
Chapter 14 : Smooth Functions on Manifolds
Chapter 15 : The Global Structure of Manifolds

Part VI : Emerging Topologies
Chapter 16 : Asynchronous Computation
Chapter 17 : Signal Models and Autoimmune Disease
Chapter 18 : Bar Code Computations in Consciousness Models

Part VII : Summing It All Up
Chapter 19 : Summing It All Up

Part VIII : References
Part IX : Detailed Index