Book Description
Mathematics for Electrical Engineering and Computing embraces many applications of modern mathematics, such as Boolean Algebra and Sets and Functions, and also teaches both discrete and continuous systems - particularly vital for Digital Signal Processing (DSP). In addition, as most modern engineers are required to study software, material suitable for Software Engineering - set theory, predicate and prepositional calculus, language and graph theory - is fully integrated into the book.
Excessive technical detail and language are avoided, recognising that the real requirement for practising engineers is the need to understand the applications of mathematics in everyday engineering contexts. Emphasis is given to an appreciation of the fundamental concepts behind the mathematics, for problem solving and undertaking critical analysis of results, whether using a calculator or a computer.
The text is backed up by numerous exercises and worked examples throughout, firmly rooted in engineering practice, ensuring that all mathematical theory introduced is directly relevant to real-world engineering. The book includes introductions to advanced topics such as Fourier analysis, vector calculus and random processes, also making this a suitable introductory text for second year undergraduates of electrical, electronic and computer engineering, undertaking engineering mathematics courses.
Dr Attenborough is a former Senior Lecturer in the School of Electrical, Electronic and Information Engineering at South Bank University. She is currently Technical Director of The Webbery - Internet development company, Co. Donegal, Ireland.- Fundamental principles of mathematics introduced and applied in engineering practice, reinforced through over 300 examples directly relevant to real-world engineering
Table of Contents
- Cover image
- Title page
- Table of Contents
- Copyright page
- Preface
- Acknowledgements
- Part 1: Sets, functions, and calculus
- 1. Sets and functions
- 1.1 Introduction
- 1.2 Sets
- 1.3 Operations on sets
- 1.4 Relations and functions
- 1.5 Combining functions
- 1.6 Summary
- 1.7 Exercises
- 2. Functions and their graphs
- 2.1 Introduction
- 2.2 The straight line: y = mx + c
- 2.3 The quadratic function: y = ax2+bx+c
- 2.4 The function y = 1/x
- 2.5 The functions y = ax
- 2.6 Graph sketching using simple transformations
- 2.7 The modulus function, y = |x| or y = abs(x)
- 2.8 Symmetry of functions and their graphs
- 2.9 Solving inequalities
- 2.10 Using graphs to find an expression for the function from experimental data
- 2.11 Summary
- 2.12 Exercises
- 3. Problem solving and the art of the convincing argument
- 3.1 Introduction
- 3.2 Describing a problem in mathematical language
- 3.3 Propositions and predicates
- 3.4 Operations on propositions and predicates
- 3.5 Equivalence
- 3.6 Implication
- 3.7 Making sweeping statements
- 3.8 Other applications of predicates
- 3.9 Summary
- 3.10 Exercises
- 4. Boolean algebra
- 4.1 Introduction
- 4.2 Algebra
- 4.3 Boolean algebras
- 4.4 Digital circuits
- 4.5 Summary
- 4.6 Exercises
- 5. Trigonometric functions and waves
- 5.1 Introduction
- 5.2 Trigonometric functions and radians
- 5.3 Graphs and important properties
- 5.4 Wave functions of time and distance
- 5.5 Trigonometric identities
- 5.6 Superposition
- 5.7 Inverse trigonometric functions
- 5.8 Solving the trigonometric equations sin x = a, cos x= a, tan x = a
- 5.9 Summary
- 5.10 Exercises
- 6. Differentiation
- 6.1 Introduction
- 6.2 The average rate of change and the gradient of a chord
- 6.3 The derivative function
- 6.4 Some common derivatives
- 6.5 Finding the derivative of combinations of functions
- 6.6 Applications of differentiation
- 6.7 Summary
- 6.9 Exercises
- 7. Integration
- 7.1 Introduction
- 7.2 Integration
- 7.3 Finding integrals
- 7.4 Applications of integration
- 7.5 The definite integral
- 7.6 The mean value and r.m.s. value
- 7.7 Numerical Methods of Integration
- 7.8 Summary
- 7.9 Exercises
- 8. The exponential function
- 8.1 Introduction
- 8.2 Exponential growth and decay
- 8.3 The exponential function y = et
- 8.4 The hyperbolic functions
- 8.5 More differentiation and integration
- 8.6 Summary
- 8.7 Exercises
- 9. Vectors
- 9.1 Introduction
- 9.2 Vectors and vector quantities
- 9.3 Addition and subtraction of vectors
- 9.4 Magnitude and direction of a 2D vector–polar co-ordinates
- 9.5 Application of vectors to represent waves (phasors)
- 9.6 Multiplication of a vector by a scalar and unit vectors
- 9.7 Basis vectors
- 9.8 Products of vectors
- 9.9 Vector equation of a line
- 9.10 Summary
- 9.12 Exercises
- 10. Complex numbers
- 10.1 Introduction
- 10.2 Phasor rotation by π/2
- 10.3 Complex numbers and operations
- 10.4 Solution of quadratic equations
- 10.5 Polar form of a complex number
- 10.6 Applications of complex numbers to AC linear circuits
- 10.7 Circular motion
- 10.8 The importance of being exponential
- 10.9 Summary
- 10.10 Exercises
- 11. Maxima and minima and sketching functions
- 11.1 Introduction
- 11.2 Stationary points, local maxima and minima
- 11.3 Graph sketching by analysing the function behaviour
- 11.4 Summary
- 11.5 Exercises
- 12. Sequences and series
- 12.1 Introduction
- 12.2 Sequences and series definitions
- 12.3 Arithmetic progression
- 12.4 Geometric progression
- 12.5 Pascal's triangle and the binomial series
- 12.6 Power series
- 12.7 Limits and convergence
- 12.8 Newton–Raphson method for solving equations
- 12.9 Summary
- 12.10 Exercises
- Part 2: Systems
- 13. Systems of linear equations, matrices, and determinants
- 13.1 Introduction
- 13.2 Matrices
- 13.3 Transformations
- 13.4 Systems of equations
- 13.5 Gauss elimination
- 13.6 The inverse and determinant of a 3 × 3 matrix
- 13.7 Eigenvectors and eigenvalues
- 13.8 Least squares data fitting
- 13.9 Summary
- 13.10 Exercises
- 14. Differential equations and difference equations
- 14.1 Introduction
- 14.2 Modelling simple systems
- 14.3 Ordinary differential equations
- 14.4 Solving first-order LTI systems
- 14.5 Solution of a second-order LTI systems
- 14.6 Solving systems of differential equations
- 14.7 Difference equations
- 14.8 Summary
- 14.9 Exercises
- 15. Laplace and z transforms
- 15.1 Introduction
- 15.2 The Laplace transform – definition
- 15.3 The unit step function and the (impulse) delta function
- 15.4 Laplace transforms of simple functions and properties of the transform
- 15.5 Solving linear differential equations with constant coefficients
- 15.6 Laplace transforms and systems theory
- 15.7 z transforms
- 15.8 Solving linear difference equations with constant coefficients using z transforms
- 15.9 z transforms and systems theory
- 15.10 Summary
- 15.11 Exercises
- 16. Fourier series
- 16.1 Introduction
- 16.2 Periodic Functions
- 16.3 Sine and cosine series
- 16.4 Fourier series of symmetric periodic functions
- 16.5 Amplitude and phase representation of a Fourier series
- 16.6 Fourier series in complex form
- 16.7 Summary
- 16.8 Exercises
- Part 3: Functions of more than one variable
- 17. Functions of more than one variable
- 17.1 Introduction
- 17.2 Functions of two variables – surfaces
- 17.3 Partial differentiation
- 17.4 Changing variables – the chain rule
- 17.5 The total derivative along a path
- 17.6 Higher-order partial derivatives
- 17.7 Summary
- 17.8 Exercises
- 18. Vector calculus
- 18.1 Introduction
- 18.2 The gradient of a scalar field
- 18.3 Differentiating vector fields
- 18.4 The scalar line integral
- 18.5 Surface integrals
- 18.6 Summary
- 18.7 Exercises
- Part 4: Graph and language theory
- 19. Graph theory
- 19.1 Introduction
- 19.2 Definitions
- 19.3 Matrix representation of a graph
- 19.4 Trees
- 19.5 The shortest path problem
- 19.6 Networks and maximum flow
- 19.7 State transition diagrams
- 19.8 Summary
- 19.9 Exercises
- 20. Language theory
- 20.1 Introduction
- 20.2 Languages and grammars
- 20.3 Derivations and derivation trees
- 20.4 Extended Backus-Naur Form (EBNF)
- 20.5 Extensible markup language (XML)
- 20.6 Summary
- 20.7 Exercises
- Part 5: Probability and statistics
- 21. Probability and statistics
- 21.1 Introduction
- 21.2 Population and sample, representation of data, mean, variance and standard deviation
- 21.3 Random systems and probability
- 21.4 Addition law of probability
- 21.5 Repeated trials, outcomes, and probabilities
- 21.6 Repeated trials and probability trees
- 21.7 Conditional probability and probability trees
- 21.8 Application of the probability laws to the probability of failure of an electrical circuit
- 21.9 Statistical modelling
- 21.10 The normal distribution
- 21.11 The exponential distribution
- 21.12 The binomial distribution
- 21.13 The Poisson distribution
- 21.14 Summary
- 21.15 Exercises
- Answers to exercises
- Chapter 1
- Chapter 2
- Chapter 3
- Chapter 4
- Chapter 5
- Chapter 6
- Chapter 7
- Chapter 8
- Chapter 9
- Chapter 10
- Chapter 11
- Chapter 12
- Chapter 13
- Chapter 14
- Chapter 15
- Chapter 16
- Chapter 17
- Chapter 18
- Chapter 19
- Chapter 20
- Chapter 21
- Index