Ebook Advanced engineering mathematics (7th edition) Part 1

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Guide to Notation

L[ f ] Laplace transform of f
L[ f ](s) Laplace transform of f evaluated at s
L−1 [F] inverse Laplace transform of F
H (t) Heaviside function
f ∗g
often denotes a convolution with respect to an integral transform, such as the Laplace
transform or the Fourier transform
δ(t) delta function
< a, b, c > vector with components a, b, c
ai + bj + ck standard form of a vector in 3-space
V
norm (magnitude, length) of a vector V
F · G dot product of vectors F and G
F × G cross product of F and G
n-space, consisting of n-vectors < x1 , x2 , · · · , xn >
Rn
[ai j ] matrix whose i, j-element is ai j . If the matrix is denoted A, this i, j element may also be
denoted Ai j
Onm
n × m zero matrix
n × n identity matrix
In
transpose of A
At
reduced (row echelon) form of A

AR
rank(A)
rank of a matrix A
.
[A..B] augmented matrix
inverse of the matrix A
A−1
|A| or det(A) determinant of A
pA (λ) characteristic polynomial of A
often denotes the fundamental matrix of a system X = AX
T often denotes a tangent vector
N often denotes a normal vector
n often denotes a unit normal vector
κ
curvature
∇
del operator
∇ϕ or grad ϕ
gradient of ϕ
Du ϕ(P) directional derivative of ϕ in the direction of u at P
f d x + g dy + h dz
line integral
C
F
·
dR
another
notation
for C f d x + g dy + h dz with F = f i + gj + hk
C

C1 C2 · · · Cn join of curves C1 , C2 , · · · , Cn
f (x, y, z) ds
line integral of f over C with respect to arc length
C
1
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2

Guide to Notation
∂( f, g)
Jacobian of f and g with respect to u and v
∂(u, v)
f (x, y, z) dσ
surface integral of f over
f (x0 −), f (x0 +) left and right limits, respectively, of f (x) at x0
F[ f ] or fˆ Fourier transform of f
ˆ

F[ f ](ω) or F(ω)
Fourier transform of f evaluated at ω
−1
inverse Fourier transform
F
Fourier cosine transform of f
FC [ f ] or fˆC
inverse Fourier cosine transform
FC−1 or fˆC−1
Fourier sine transform of f
F S [ f ] or fˆS
inverse Fourier sine transform
F S−1 or fˆS−1
D[u] discrete N - point Fourier transform (DFT) of a sequence u j
windowed Fourier transform
fˆwin
often denotes the characteristic function of an interval I
χI
σ N (t) often denotes the N th Cesàro sum of a Fourier series
Z (t) in the context of filtering, denotes a filter function
Pn (x) nth Legendre polynomial
(x) gamma function
B(x, y) beta function
Bessel function of the first kind of order ν
Jν
γ
depending on context, may denote Euler’s constant
Bessel function of the second kind of order ν
Yν
modified Bessel functions of the first and second kinds, respectively, of order zero

I0 , K 0
Laplacian of u
∇ 2u
Re(z) real part of a complex number z
Im(z) imaginary part of a complex number z
z
complex conjugate of z
|z| magnitude (also norm or modulus) of z
arg(z) argument of z
f (z) dz
integral of a complex function f (z) over a curve C
C
f
(z)
dz
integral of f over a closed curve C
C
Res( f, z 0 ) residue of f (z) at z 0
f : D → D∗
f is a mapping from D to D ∗

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A D VA N C E D
ENGINEERING
M AT H E M AT I C S

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Advanced Engineering Mathematics
Seventh Edition
Peter V. O’Neil
Publisher, Global Engineering:
Christopher M. Shortt
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A D VA N C E D
ENGINEERING
M AT H E M AT I C S
7th Edition

PETER V. O’NEIL
The University of Alabama
at Birmingham

Australia · Brazil · Japan · Korea · Mexico · Singapore · Spain · United Kingdom · United States

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Contents
Preface xi

PART

1

CHAPTER 1

Ordinary Differential Equations 1
First-Order Differential Equations

3

1.1
1.2
1.3
1.4

Terminology and Separable Equations 3
Linear Equations 16
Exact Equations 21
Homogeneous, Bernoulli, and Riccati Equations 26

1.4.1 The Homogeneous Differential Equation 26
1.4.2 The Bernoulli Equation 27
1.4.3 The Riccati Equation 28
1.5 Additional Applications 30
1.6 Existence and Uniqueness Questions 40

CHAPTER 2

Linear Second-Order Equations

43

2.1 The Linear Second-Order Equation 43
2.2 The Constant Coefficient Case 50
2.3 The Nonhomogeneous Equation 55
2.3.1 Variation of Parameters 55
2.3.2 Undetermined Coefficients 57
2.3.3 The Principle of Superposition 60
2.4 Spring Motion 61
2.4.1 Unforced Motion 62
2.4.2 Forced Motion 66
2.4.3 Resonance 67
2.4.4 Beats 69
2.4.5 Analogy with an Electrical Circuit 70
2.5 Euler’s Differential Equation 72

CHAPTER 3

The Laplace Transform

77

3.1 Definition and Notation 77
3.2 Solution of Initial Value Problems 81
3.3 Shifting and the Heaviside Function 84
v
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vi

Contents

3.4
3.5
3.6
3.7

CHAPTER 4

3.3.1 The First Shifting Theorem 84
3.3.2 The Heaviside Function and Pulses 86
3.3.3 Heaviside’s Formula 93
Convolution 96
Impulses and the Delta Function 102
Solution of Systems 106
Polynomial Coefficients 112
3.7.1 Differential Equations with Polynomial Coefficients
3.7.2 Bessel Functions 114

Series Solutions

112

121

4.1 Power Series Solutions 121
4.2 Frobenius Solutions 126

CHAPTER 5

Approximation of Solutions

137

5.1 Direction Fields 137
5.2 Euler’s Method 139
5.3 Taylor and Modified Euler Methods

PART

2

CHAPTER 6

Vectors, Linear Algebra, and Systems
of Linear Differential Equations 145
Vectors and Vector Spaces 147
6.1
6.2
6.3
6.4
6.5
6.6
6.7

CHAPTER 7

142

Vectors in the Plane and 3-Space 147
The Dot Product 154
The Cross Product 159
The Vector Space R n 162
Orthogonalization 175
Orthogonal Complements and Projections
The Function Space C[a, b] 181

177

Matrices and Linear Systems 187
7.1

7.2
7.3
7.4
7.5
7.6
7.7
7.8
7.9
7.10

Matrices 187
7.1.1 Matrix Multiplication from Another Perspective 191
7.1.2 Terminology and Special Matrices 192
7.1.3 Random Walks in Crystals 194
Elementary Row Operations 198
Reduced Row Echelon Form 203
Row and Column Spaces 208
Homogeneous Systems 213
Nonhomogeneous Systems 220
Matrix Inverses 226
Least Squares Vectors and Data Fitting 232
LU Factorization 237
Linear Transformations 240

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Contents

CHAPTER 8

Determinants 247
8.1
8.2
8.3
8.4
8.5
8.6

CHAPTER 9

vii

Definition of the Determinant 247
Evaluation of Determinants I 252

Evaluation of Determinants II 255
A Determinant Formula for A−1 259
Cramer’s Rule 260
The Matrix Tree Theorem 262

Eigenvalues, Diagonalization, and Special Matrices 267
9.1 Eigenvalues and Eigenvectors 267
9.2 Diagonalization 277
9.3 Some Special Types of Matrices 284
9.3.1 Orthogonal Matrices 284
9.3.2 Unitary Matrices 286
9.3.3 Hermitian and Skew-Hermitian Matrices 288
9.3.4 Quadratic Forms 290

CHAPTER 10 Systems of Linear Differential Equations

295

10.1 Linear Systems 295
10.1.1 The Homogeneous System X = AX. 296
10.1.2 The Nonhomogeneous System 301
10.2 Solution of X = AX for Constant A 302
10.2.1 Solution When A Has a Complex Eigenvalue 306
10.2.2 Solution When A Does Not Have n Linearly Independent Eigenvectors 308
10.3 Solution of X = AX + G 312
10.3.1 Variation of Parameters 312
10.3.2 Solution by Diagonalizing A 314
10.4 Exponential Matrix Solutions 316
10.5 Applications and Illustrations of Techniques 319
10.6 Phase Portraits 329

10.6.1 Classification by Eigenvalues 329
10.6.2 Predator/Prey and Competing Species Models 338

PART

3

Vector Analysis 343

CHAPTER 11 Vector Differential Calculus 345
11.1
11.2
11.3
11.4

Vector Functions of One Variable 345
Velocity and Curvature 349
Vector Fields and Streamlines 354
The Gradient Field 356
11.4.1 Level Surfaces, Tangent Planes, and Normal Lines
11.5 Divergence and Curl 362
11.5.1 A Physical Interpretation of Divergence 364
11.5.2 A Physical Interpretation of Curl 365

359

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Contents

CHAPTER 12 Vector Integral Calculus 367
12.1
12.2
12.3
12.4
12.5

12.6

12.7
12.8

12.9

12.10

PART

4

Line Integrals 367
12.1.1 Line Integral With Respect to Arc Length 372
Green’s Theorem 374
An Extension of Green’s Theorem 376
Independence of Path and Potential Theory 380
Surface Integrals 388
12.5.1 Normal Vector to a Surface 389
12.5.2 Tangent Plane to a Surface 392
12.5.3 Piecewise Smooth Surfaces 392
12.5.4 Surface Integrals 393
Applications of Surface Integrals 395
12.6.1 Surface Area 395
12.6.2 Mass and Center of Mass of a Shell 395
12.6.3 Flux of a Fluid Across a Surface 397
Lifting Green’s Theorem to R 3 399
The Divergence Theorem of Gauss 402
12.8.1 Archimedes’s Principle 404
12.8.2 The Heat Equation 405
Stokes’s Theorem 408
12.9.1 Potential Theory in 3-Space 410
12.9.2 Maxwell’s Equations 411
Curvilinear Coordinates 414

Fourier Analysis, Special Functions,
and Eigenfunction Expansions 425

CHAPTER 13 Fourier Series 427
13.1
13.2

13.3

13.4
13.5
13.6
13.7

Why Fourier Series? 427
The Fourier Series of a Function 429
13.2.1 Even and Odd Functions 436
13.2.2 The Gibbs Phenomenon 438
Sine and Cosine Series 441
13.3.1 Cosine Series 441
13.3.2 Sine Series 443
Integration and Differentiation of Fourier Series 445
Phase Angle Form 452
Complex Fourier Series 457
Filtering of Signals 461

CHAPTER 14 The Fourier Integral and Transforms
14.1
14.2
14.3

465

The Fourier Integral 465
Fourier Cosine and Sine Integrals 468
The Fourier Transform 470
14.3.1 Filtering and the Dirac Delta Function 481
14.3.2 The Windowed Fourier Transform 483

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Contents

14.4
14.5

14.6
14.7

ix

14.3.3 The Shannon Sampling Theorem 485
14.3.4 Low-Pass and Bandpass Filters 487
Fourier Cosine and Sine Transforms 490
The Discrete Fourier Transform 492
14.5.1 Linearity and Periodicity of the DFT 494
14.5.2 The Inverse N -Point DFT 494
14.5.3 DFT Approximation of Fourier Coefficients 495
Sampled Fourier Series 498
DFT Approximation of the Fourier Transform 501

CHAPTER 15 Special Functions and Eigenfunction Expansions

505

15.1 Eigenfunction Expansions 505
15.1.1 Bessel’s Inequality and Parseval’s Theorem 515
15.2 Legendre Polynomials 518
15.2.1 A Generating Function for Legendre Polynomials 521
15.2.2 A Recurrence Relation for Legendre Polynomials 523
15.2.3 Fourier-Legendre Expansions 525
15.2.4 Zeros of Legendre Polynomials 528
15.2.5 Distribution of Charged Particles 530
15.2.6 Some Additional Results 532
15.3 Bessel Functions 533
15.3.1 The Gamma Function 533
15.3.2 Bessel Functions of the First Kind 534
15.3.3 Bessel Functions of the Second Kind 538
15.3.4 Displacement of a Hanging Chain 540
15.3.5 Critical Length of a Rod 542
15.3.6 Modified Bessel Functions 543

15.3.7 Alternating Current and the Skin Effect 546
15.3.8 A Generating Function for Jν (x) 548
15.3.9 Recurrence Relations 549
15.3.10 Zeros of Bessel Functions 550
15.3.11 Fourier-Bessel Expansions 552
15.3.12 Bessel’s Integrals and the Kepler Problem 556

PART

5

Partial Differential Equations 563

CHAPTER 16 The Wave Equation

565

16.1 Derivation of the Wave Equation 565
16.2 Wave Motion on an Interval 567
16.2.1 Zero Initial Velocity 568
16.2.2 Zero Initial Displacement 570
16.2.3 Nonzero Initial Displacement and Velocity 572
16.2.4 Influence of Constants and Initial Conditions 573
16.2.5 Wave Motion with a Forcing Term 575

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x

Contents
16.3
16.4
16.5
16.6

16.7
16.8
16.9

Wave Motion in an Infinite Medium 579
Wave Motion in a Semi-Infinite Medium 585
16.4.1 Solution by Fourier Sine or Cosine Transform
Laplace Transform Techniques 587
Characteristics and d’Alembert’s Solution 594
16.6.1 Forward and Backward Waves 596
16.6.2 Forced Wave Motion 599
Vibrations in a Circular Membrane I 602
16.7.1 Normal Modes of Vibration 604

Vibrations in a Circular Membrane II 605
Vibrations in a Rectangular Membrane 608

CHAPTER 17 The Heat Equation

586

611

17.1 Initial and Boundary Conditions 611
17.2 The Heat Equation on [0, L] 612
17.2.1 Ends Kept at Temperature Zero 612
17.2.2 Insulated Ends 614
17.2.3 Radiating End 615
17.2.4 Transformation of Problems 618
17.2.5 The Heat Equation with a Source Term 619
17.2.6 Effects of Boundary Conditions and Constants
17.3 Solutions in an Infinite Medium 626
17.3.1 Problems on the Real Line 626
17.3.2 Solution by Fourier Transform 627
17.3.3 Problems on the Half-Line 629
17.3.4 Solution by Fourier Sine Transform 630
17.4 Laplace Transform Techniques 631
17.5 Heat Conduction in an Infinite Cylinder 636
17.6 Heat Conduction in a Rectangular Plate 638

CHAPTER 18 The Potential Equation

622

641

18.1 Laplace’s Equation 641
18.2 Dirichlet Problem for a Rectangle 642
18.3 Dirichlet Problem for a Disk 645
18.4 Poisson’s Integral Formula 648
18.5 Dirichlet Problem for Unbounded Regions 649
18.5.1 The Upper Half-Plane 650
18.5.2 The Right Quarter-Plane 652
18.6 A Dirichlet Problem for a Cube 654
18.7 Steady-State Equation for a Sphere 655
18.8 The Neumann Problem 659
18.8.1 A Neumann Problem for a Rectangle 660
18.8.2 A Neumann Problem for a Disk 662
18.8.3 A Neumann Problem for the Upper Half-Plane 664

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Contents

PART

6

xi

Complex Functions 667

CHAPTER 19 Complex Numbers and Functions

669

19.1 Geometry and Arithmetic of Complex Numbers 669
19.2 Complex Functions 676
19.2.1 Limits, Continuity, and Differentiability 677
19.2.2 The Cauchy-Riemann Equations 680
19.3 The Exponential and Trigonometric Functions 684
19.4 The Complex Logarithm 689
19.5 Powers 690

CHAPTER 20 Complex Integration
20.1
20.2
20.3

695

The Integral of a Complex Function 695

Cauchy’s Theorem 700
Consequences of Cauchy’s Theorem 703
20.3.1 Independence of Path 703
20.3.2 The Deformation Theorem 704
20.3.3 Cauchy’s Integral Formula 706
20.3.4 Properties of Harmonic Functions 709
20.3.5 Bounds on Derivatives 710
20.3.6 An Extended Deformation Theorem 711
20.3.7 A Variation on Cauchy’s Integral Formula 713

CHAPTER 21 Series Representations of Functions
21.1 Power Series 715
21.2 The Laurent Expansion

715

725

CHAPTER 22 Singularities and the Residue Theorem 729
22.1 Singularities 729
22.2 The Residue Theorem 733
22.3 Evaluation of Real Integrals 740
22.3.1 Rational Functions 740
22.3.2 Rational Functions Times Cosine or Sine 742
22.3.3 Rational Functions of Cosine and Sine 743
22.4 Residues and the Inverse Laplace Transform 746
22.4.1 Diffusion in a Cylinder 748

CHAPTER 23 Conformal Mappings and Applications

751

23.1 Conformal Mappings 751
23.2 Construction of Conformal Mappings 765
23.2.1 The Schwarz-Christoffel Transformation

773

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Contents
23.3
23.4

Conformal Mapping Solutions of Dirichlet Problems
Models of Plane Fluid Flow 779

776

APPENDIX A MAPLE Primer 789
Answers to Selected Problems 801
Index 867

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Preface
This seventh edition of Advanced Engineering Mathematics differs from the sixth in four ways.
First, based on reviews and user comments, new material has been added, including the
following.
• Orthogonal projections and least squares approximations of vectors and functions. This provides a unifying theme in recognizing partial sums of eigenfunction expansions as projections
onto subspaces, as well as understanding lines of best fit to data points.
• Orthogonalization and the production of orthogonal bases.
• LU factorization of matrices.
• Linear transformations and matrix representations.

• Application of the Laplace transform to the solution of Bessel’s equation and to problems
involving wave motion and diffusion.
• Expanded treatment of properties and applications of Legendre polynomials and Bessel
functions, including a solution of Kepler’s problem and a model of alternating current flow.
• Heaviside’s formula for the computation of inverse Laplace transforms.
• A complex integral formula for the inverse Laplace transform, including an application to heat
diffusion in a slab.
• Vector operations in orthogonal curvilinear coordinates.
• Application of vector integral theorems to the development of Maxwell’s equations.
• An application of the Laplace transform convolution to a replacement scheduling problem.
The second new feature of this edition is the interaction of the text with MapleTM . An
appendix (called A Maple Primer) is included on the use of MapleTM and references to the use of
MapleTM are made throughout the text.
Third, there is an added emphasis on constructing and analyzing models, using ordinary and
partial differential equations, integral transforms, special functions, eigenfunction expansions,
and matrix and complex function methods.
Finally, the answer section in the back of the book has been expanded to provide more
information to the student.
This edition is also shorter and more convenient to use than preceding editions. The chapters
comprising Part 8 of the Sixth Edition, Counting and Probability, and Statistics, are now available
on the 7e book website for instructors and students.
Supplements for Instructors:
• A detailed and completely revised Instructor’s Solutions Manual and
• PowerPoint Slides
are available through the Instructor’s Resource site at login.cengage.com.
xiii
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P reface
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PETER V. O’NEIL

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PA R T

1
Ordinary
Differential
Equations

CHAPTER 1
First-Order Differential
Equations

CHAPTER 2

Linear Second-Order
Equations

CHAPTER 3
The Laplace Transform

CHAPTER 4
Series Solutions

CHAPTER 5
Approximation of Solutions

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CHAPTER

1

T E R M I N O L O G Y A N D S E PA R A B L E E Q U AT I O N S
L I N E A R E Q U AT I O N S E X A C T E Q U AT I O N S
H O M O G E N E O U S B E R N O U L L I A N D R I C C AT I
E Q U AT I O N S E X I S T E N C E A N D U N I Q U E N E S S

First-Order
Differential
Equations

1.1

Terminology and Separable Equations
Part 1 of this book deals with ordinary differential equations, which are equations that contain
one or more derivatives of a function of a single variable. Such equations can be used to model a
rich variety of phenomena of interest in the sciences, engineering, economics, ecological studies,
and other areas.
We begin in this chapter with first-order differential equations, in which only the first
derivative of the unknown function appears. As an example,
y + xy = 0
is a first-order equation for the unknown function y(x). A solution of a differential equation is
2
any function satisfying the equation. It is routine to check by substitution that y = ce−x /2 is a
solution of y + x y = 0 for any constant c.
We will develop techniques for solving several kinds of first-order equations which arise in
important contexts, beginning with separable equations.

A differential equation is separable if it can be written (perhaps after some algebraic
manipulation) as
dy
= F(x)G(y)

dx
in which the derivative equals a product of a function just of x and a function just of y.
This suggests a method of solution.

3
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4

CHAPTER 1 First-Order Differential Equations
Step 1. For y such that G(y) = 0, write the differential form
1
dy = F(x) d x.
G(y)
In this equation, we say that the variables have been separated.
Step 2. Integrate
1
dy =

G(y)

F(x) d x.

Step 3. Attempt to solve the resulting equation for y in terms of x. If this is possible, we have
an explicit solution (as in Examples 1.1 through 1.3). If this is not possible, the solution
is implicitly defined by an equation involving x and y (as in Example 1.4).
Step 4. Following this, go back and check the differential equation for any values of y such that
G(y) = 0. Such values of y were excluded in writing 1/G(y) in step (1) and may lead
to additional solutions beyond those found in step (3). This happens in Example 1.1.

EXAMPLE 1.1

To solve y = y 2 e−x , first write
dy
= y 2 e−x .
dx
If y = 0, this has the differential form
1
dy = e−x d x.
y2
The variables have been separated. Integrate
1
dy =
y2

e−x d x

or
1

− = −e−x + k
y
in which k is a constant of integration. Solve for y to get
y(x) =

1
.
e −k
−x

This is a solution of the differential equation for any number k.
Now go back and examine the assumption y = 0 that was needed to separate the variables.
Observe that y = 0 by itself satisfies the differential equation, hence it provides another solution
(called a singular solution).
In summary, we have the general solution
y(x) =

1
e−x − k

for any number k as well as a singular solution y = 0, which is not contained in the general
solution for any choice of k.
This expression for y(x) is called the general solution of this differential equation because
it contains an arbitrary constant. We obtain particular solutions by making specific choices for
k. In Example 1.1,

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1.1 Terminology and Separable Equations

5

2

1.5

1

0.5

0
–0.6

–0.4

–0.2

x

0

0.2

0.4

0.6

–0.5

–1
FIGURE 1.1

Some integral curves from Example 1.1.

1
1
, y(x) = −x
,
e −3
e +3
1
1
, and y(x) = −x = e x
y(x) = −x
e −6
e
are particular solutions corresponding to k = ±3, 6, and 0. Particular solutions are also called
integral curves of the differential equation. Graphs of these integral curves are shown in
Figure 1.1.

y(x) =

−x

EXAMPLE 1.2

x 2 y = 1 + y is separable, since we can write
1
1
dy = 2 d x
1+ y
x
if y = −1 and x = 0. Integrate to obtain
1
ln |1 + y| = − + k
x
with k an arbitrary constant. This equation implicitly defines the solution. For a given k, we have
an equation for the solution corresponding to that k, but not yet an explicit expression for this
solution. In this example, we can explicitly solve for y(x). First, take the exponential of both
sides of the equation to get
|1 + y| = ek e−1/x = ae−1/x ,
where we have written a = ek . Since k can be any number, a can be any positive number.
Eliminate the absolute value symbol by writing
1 + y = ±ae−1/x = be−1/x ,
where the constant b = ±a can be any nonzero number. Then
y = −1 + be−1/x
with b = 0.

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