Atnaujinkite slapukų nuostatas

Differential Equations: Techniques, Theory, and Applications [Kietas viršelis]

  • Formatas: Hardback, 880 pages, aukštis x plotis: 279x216 mm, weight: 2235 g
  • Serija: Monograph Books
  • Išleidimo metai: 30-Nov-2019
  • Leidėjas: American Mathematical Society
  • ISBN-10: 1470447975
  • ISBN-13: 9781470447977
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 880 pages, aukštis x plotis: 279x216 mm, weight: 2235 g
  • Serija: Monograph Books
  • Išleidimo metai: 30-Nov-2019
  • Leidėjas: American Mathematical Society
  • ISBN-10: 1470447975
  • ISBN-13: 9781470447977
Kitos knygos pagal šią temą:
Differential Equations: Techniques, Theory, and Applications is designed for a modern first course in differential equations either one or two semesters in length. The organization of the book interweaves the three components in the subtitle, with each building on and supporting the others. Techniques include not just computational methods for producing solutions to differential equations, but also qualitative methods for extracting conceptual information about differential equations and the systems modeled by them. Theory is developed as a means of organizing, understanding, and codifying general principles. Applications show the usefulness of the subject as a whole and heighten interest in both solution techniques and theory. Formal proofs are included in cases where they enhance core understanding; otherwise, they are replaced by informal justifications containing key ideas of a proof in a more conversational format. Applications are drawn from a wide variety of fields: those in physical science and engineering are prominent, of course, but models from biology, medicine, ecology, economics, and sports are also featured.

The 1,400 exercises are especially compelling. They range from routine calculations to large-scale projects. The more difficult problems, both theoretical and applied, are typically presented in manageable steps. The hundreds of meticulously detailed modeling problems were deliberately designed along pedagogical principles found especially effective in the MAA study Characteristics of Successful Calculus Programs, namely, that asking students to work problems that require them to grapple with concepts (or even proofs) and do modeling activities is key to successful student experiences and retention in STEM programs. The exposition itself is exceptionally readable, rigorous yet conversational. Students will find it inviting and approachable. The text supports many different styles of pedagogy from traditional lecture to a flipped classroom model. The availability of a computer algebra system is not assumed, but there are many opportunities to incorporate the use of one.
Preface ix
Chapter 1 Introduction
1(24)
1.1 What is a differential equation?
1(1)
1.2 What is a solution?
2(14)
1.3 More on direction fields: Isoclines
16(9)
Chapter 2 First-Order Equations
25(114)
2.1 Linear equations
25(10)
2.2 Separable equations
35(10)
2.3 Applications: Time of death, time at depth, and ancient timekeeping
45(20)
2.4 Existence and uniqueness theorems
65(18)
2.5 Population and financial models
83(15)
2.6 Qualitative solutions of autonomous equations
98(14)
2.7 Change of variable
112(9)
2.8 Exact equations
121(18)
Chapter 3 Numerical Methods
139(32)
3.1 Euler's method
139(12)
3.2 Improving Euler's method: The Heun and Runge-Kutta Algorithms
151(11)
3.3 Optical illusions and other applications
162(9)
Chapter 4 Higher-Order Linear Homogeneous Equations
171(94)
4.1 Introduction to second-order equations
171(21)
4.2 Linear operators
192(17)
4.3 Linear independence
209(7)
4.4 Constant coefficient second-order equations
216(12)
4.5 Repeated roots and reduction of order
228(12)
4.6 Higher-order equations
240(5)
4.7 Higher-order constant coefficient equations
245(9)
4.8 Modeling with second-order equations
254(11)
Chapter 5 Higher-Order Linear Nonhomogeneous Equations
265(54)
5.1 Introduction to nonhomogeneous equations
265(10)
5.2 Annihilating operators
275(13)
5.3 Applications of nonhomogeneous equations
288(15)
5.4 Electric circuits
303(16)
Chapter 6 Laplace Transforms
319(62)
6.1 Laplace transforms
319(11)
6.2 The inverse Laplace transform
330(5)
6.3 Solving initial value problems with Laplace transforms
335(15)
6.4 Applications
350(7)
6.5 Laplace transforms, simple systems, and Iwo Jima
357(6)
6.6 Convolutions
363(5)
6.7 The delta function
368(13)
Chapter 7 Power Series Solutions
381(62)
7.1 Motivation for the study of power series solutions
381(2)
7.2 Review of power series
383(9)
7.3 Series solutions
392(16)
7.4 Nonpolynomial coefficients
408(5)
7.5 Regular singular points
413(17)
7.6 Bessel's equation
430(13)
Chapter 8 Linear Systems I
443(120)
8.1 Nelson at Trafalgar and phase portraits
443(14)
8.2 Vectors, vector fields, and matrices
457(15)
8.3 Eigenvalues and eigenvectors
472(10)
8.4 Solving linear systems
482(13)
8.5 Phase portraits via ray solutions
495(12)
8.6 More on phase portraits: Saddle points and nodes
507(17)
8.7 Complex and repeated eigenvalues
524(12)
8.8 Applications: Compartment models
536(13)
8.9 Classifying equilibrium points
549(14)
Chapter 9 Linear Systems II
563(52)
9.1 The matrix exponential, Part I
563(17)
9.2 A return to the Existence and Uniqueness Theorem
580(4)
9.3 The matrix exponential, Part II
584(11)
9.4 Nonhomogeneous constant coefficient systems
595(13)
9.5 Periodic forcing and the steady-state solution
608(7)
Chapter 10 Nonlinear Systems
615(102)
10.1 Introduction: Darwin's finches
615(12)
10.2 Linear approximation: The major cases
627(20)
10.3 Linear approximation: The borderline cases
647(6)
10.4 More on interacting populations
653(15)
10.5 Modeling the spread of disease
668(15)
10.6 Hamiltonians, gradient systems, and Lyapunov functions
683(16)
10.7 Pendulums
699(9)
10.8 Cycles and limit cycles
708(9)
Chapter 11 Partial Differential Equations and Fourier Series
717(116)
11.1 Introduction: Three interesting partial differential equations
717(2)
11.2 Boundary value problems
719(8)
11.3 Partial differential equations: A first look
727(7)
11.4 Advection and diffusion
734(11)
11.5 Functions as vectors
745(15)
11.6 Fourier series
760(17)
11.7 The heat equation
777(15)
11.8 The wave equation: Separation of variables
792(12)
11.9 The wave equation: D'Alembert's method
804(8)
11.10 Laplace's equation
812(21)
Notes and Further Reading 833(4)
Selected Answers to Exercises 837(26)
Bibliography 863(4)
Index 867
Barbara D. MacCluer, University of Virginia, Charlottesville, VA.

Paul S. Bourdon, University of Virginia, Charlottesville, VA.

Thomas L. Kriete, University of Virginia, Charlottesville, VA.